David Menninger's Analyst Perspectives | IT Performance Management (ITPM)

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Intelligence</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/analytics-and-data/data-operations" class="minimal-mobile-menu-link"><span>Data Operations</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/analytics-and-data/data-platforms" class="minimal-mobile-menu-link"><span>Data Platforms</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/analytics-and-data/streaming-and-events" class="minimal-mobile-menu-link"><span>Streaming & Events</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/artificial-intelligence" class="minimal-mobile-menu-link"><span>Artificial Intelligence</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/artificial-intelligence/computer-vision" class="minimal-mobile-menu-link"><span>Computer Vision</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.ventanaresearch.com/focus/artificial-intelligence/deep-learning" class="minimal-mobile-menu-link"><span>Deep Learning</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/artificial-intelligence/generative-ai" class="minimal-mobile-menu-link"><span>Generative AI</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/artificial-intelligence/mlops" class="minimal-mobile-menu-link"><span>Machine Learning Operations</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/artificial-intelligence/model-building-and-llm" class="minimal-mobile-menu-link"><span>Model Building & Large Language Models</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/artificial-intelligence/natural-language-processing" class="minimal-mobile-menu-link"><span>Natural Language Processing</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/customerexperience" class="minimal-mobile-menu-link"><span>Customer Experience</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/agentmanagement" class="minimal-mobile-menu-link"><span>Agent Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/contactcenter" class="minimal-mobile-menu-link"><span>Contact Center</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/customerexperiencemanagement" class="minimal-mobile-menu-link"><span>Customer Experience Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/fieldservice" class="minimal-mobile-menu-link"><span>Field Service</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/intelligentselfservice" class="minimal-mobile-menu-link"><span>Intelligent Self-Service</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/voiceofthecustomer" class="minimal-mobile-menu-link"><span>Voice of the Customer</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/digitalbusiness" class="minimal-mobile-menu-link"><span>Digital Business</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/digital-applications" class="minimal-mobile-menu-link"><span>Digital Applications</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/digitalcommunications" class="minimal-mobile-menu-link"><span>Digital Communications</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/digital-intelligence" class="minimal-mobile-menu-link"><span>Digital Intelligence</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/digital-operations" class="minimal-mobile-menu-link"><span>Digital Operations</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/experiencemanagement" class="minimal-mobile-menu-link"><span>Experience Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/generative-ai" class="minimal-mobile-menu-link"><span>Generative AI</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/performancemanagement" class="minimal-mobile-menu-link"><span>Performance Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/sustainabilityandesg" class="minimal-mobile-menu-link"><span>Sustainability & ESG</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/workmanagement" class="minimal-mobile-menu-link"><span>Work Management</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/digitaltechnology" class="minimal-mobile-menu-link"><span>Digital Technology</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/businesscontinuity" class="minimal-mobile-menu-link"><span>Business Continuity</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/cloudcomputing" class="minimal-mobile-menu-link"><span>Cloud Computing</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/devops" class="minimal-mobile-menu-link"><span>DevOps and Platforms</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/digitalsecurity" class="minimal-mobile-menu-link"><span>Digital Security</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/intelligentautomation" class="minimal-mobile-menu-link"><span>Intelligent Automation</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/internetofthings" class="minimal-mobile-menu-link"><span>IoT and Edge Computing</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/itops" class="minimal-mobile-menu-link"><span>ITOps</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/it-service-management" class="minimal-mobile-menu-link"><span>IT Service Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitaltechnology/observability" class="minimal-mobile-menu-link"><span>Observability</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/humancapitalmanagement" class="minimal-mobile-menu-link"><span>Human Capital Management</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/humancapitalmanagement/employeeexperience" class="minimal-mobile-menu-link"><span>Employee Experience</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/humancapitalmanagement/learningmanagement" class="minimal-mobile-menu-link"><span>Learning Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/humancapitalmanagement/payrollmanagement" class="minimal-mobile-menu-link"><span>Payroll Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/humancapitalmanagement/talentmanagement" class="minimal-mobile-menu-link"><span>Talent Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/humancapitalmanagement/totalcompensationmanagement" class="minimal-mobile-menu-link"><span>Total Compensation Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/humancapitalmanagement/workforcemanagement" class="minimal-mobile-menu-link"><span>Workforce Management</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/marketing" class="minimal-mobile-menu-link"><span>Marketing</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/marketing/customerdataplatforms" class="minimal-mobile-menu-link"><span>Customer Data Platforms</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/marketing/digitalexperienceplatforms" class="minimal-mobile-menu-link"><span>Digital Experience Platform</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/marketing/digitalmarketing" class="minimal-mobile-menu-link"><span>Digital Marketing</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/marketing/intelligentmarketing" class="minimal-mobile-menu-link"><span>Intelligent Marketing</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/marketing/marketingperformancemanagement" class="minimal-mobile-menu-link"><span>Marketing Performance Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/marketing/productexperiencemanagement" class="minimal-mobile-menu-link"><span>Product Experience Management</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/officeoffinance" class="minimal-mobile-menu-link"><span>Office of Finance</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeoffinance/businessplanning" class="minimal-mobile-menu-link"><span>Business Planning</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeoffinance/digitalfinance" class="minimal-mobile-menu-link"><span>Digital Finance</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeoffinance/erpandcontinuousaccounting" class="minimal-mobile-menu-link"><span>ERP & Continuous Accounting</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeoffinance/consolidate-and-close-management" class="minimal-mobile-menu-link"><span>Consolidate & Close Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeoffinance/procure-to-pay" class="minimal-mobile-menu-link"><span>Procure-to-Pay</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeoffinance/order-to-cash" class="minimal-mobile-menu-link"><span>Order-to-Cash</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/officeofrevenue" class="minimal-mobile-menu-link"><span>Office of Revenue</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeofrevenue/digitalcommerce" class="minimal-mobile-menu-link"><span>Digital Commerce</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeofrevenue/partnermanagement" class="minimal-mobile-menu-link"><span>Partner Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeofrevenue/revenuemanagement" class="minimal-mobile-menu-link"><span>Revenue Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeofrevenue/revenueperformancemanagement" class="minimal-mobile-menu-link"><span>Revenue Performance Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeofrevenue/salesengagement" class="minimal-mobile-menu-link"><span>Sales Engagement</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/officeofrevenue/subscriptionmanagement" class="minimal-mobile-menu-link"><span>Subscription Management</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/operationsandsupplychain" class="minimal-mobile-menu-link"><span>Operations & Supply Chain</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/operationsandsupplychain/continuousplanning" class="minimal-mobile-menu-link"><span>Continuous Planning</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/operationsandsupplychain/continuousupplychainanderp" class="minimal-mobile-menu-link"><span>Continuous Supply Chain & ERP</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/operationsandsupplychain/productinformationmanagement" class="minimal-mobile-menu-link"><span>Product Information Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/operationsandsupplychain/propertytechnology" class="minimal-mobile-menu-link"><span>Property Technology</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/operationsandsupplychain/supplierrelationshipmanagement" class="minimal-mobile-menu-link"><span>Supplier Relationship Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/operationsandsupplychain/sustainabilitymanagement" class="minimal-mobile-menu-link"><span>Sustainability Management</span></a></span> </li> </ul> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industries" class="minimal-mobile-menu-link"><span>Industries</span></a></span> <ul class="minimal-mobile-menu-submenu level-2"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/automotive" class="minimal-mobile-menu-link"><span>Automotive</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/banking" class="minimal-mobile-menu-link"><span>Banking</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/consumer-products" class="minimal-mobile-menu-link"><span>Consumer Products</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/financial-services" class="minimal-mobile-menu-link"><span>Financial Services</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/food-beverage" class="minimal-mobile-menu-link"><span>Food & Beverage</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/healthcare" class="minimal-mobile-menu-link"><span>Healthcare</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/hospitality" class="minimal-mobile-menu-link"><span>Hospitality</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/insurance" class="minimal-mobile-menu-link"><span>Insurance</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/manufacturing" class="minimal-mobile-menu-link"><span>Manufacturing</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/media-entertainment" class="minimal-mobile-menu-link"><span>Media & Entertainment</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/real-estate" class="minimal-mobile-menu-link"><span>Real Estate</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/vertical-industry/retail" class="minimal-mobile-menu-link"><span>Retail</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/research" class="minimal-mobile-menu-link"><span>Research</span></a></span> <ul class="minimal-mobile-menu-submenu level-2"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/research/market-agendas" class="minimal-mobile-menu-link"><span>Market Agendas</span></a></span> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://blog.ventanaresearch.com/" class="minimal-mobile-menu-link"><span>Analyst Perspectives</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://davidmenninger.ventanaresearch.com/" class="minimal-mobile-menu-link"><span>David Menninger</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://jefforr.ventanaresearch.com/" class="minimal-mobile-menu-link"><span>Jeff Orr</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://keithdawson.isg-research.net" class="minimal-mobile-menu-link"><span>Keith Dawson</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://marksmith.ventanaresearch.com/" class="minimal-mobile-menu-link"><span>Mark Smith</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://mattaslett.isg-research.net" class="minimal-mobile-menu-link"><span>Matt Aslett</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://matthewbrown.isg-research.net" class="minimal-mobile-menu-link"><span>Matthew Brown</span></a></span> </li> <li 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We offer a portfolio of advisory, research, thought leadership and digital education services to help optimize market strategy, planning and execution.</p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/analyst_relations" rel="noopener">Analyst Relations</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/demand_generation" rel="noopener">Demand Generation</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/product-marketing" rel="noopener">Product Marketing</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/vendor-coverage" target="_self" role="menuitem">Market Coverage</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/briefing" target="_self" role="menuitem">Request a Briefing</a></strong><br><br><br></p></div> <span id="hs_cos_wrapper_dnd_area-module-2_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_simple_menu" style="" data-hs-cos-general-type="widget" data-hs-cos-type="simple_menu"><ul></ul></span> <div class="bottom_rich_text"> </div> </div> </div> </div> </div> </div> <script src="https://davidmenninger.isg-research.net/hs-fs/hub/2035844/hub_generated/template_assets/90531223305/1725882478811/Ventana_Research_2023/js/mmenu.min.js"></script> </div> </div> </div> </div> </div> </div> </div> </div> <div id="hs_cos_wrapper_Structured_data" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"></div> <div class="body-container-wrapper"> <div class="blog-header background-image post_page_2" data-bg-color="secondary" style=" background-size:cover; background-position:50%; background-repeat:no-repeat; background-image:url(https://davidmenninger.isg-research.net/hubfs/_images/_backgrounds_expertise/2024_VR_AI_Expertise_Image_AdobeStock_637057734_1200px.jpg); ">  <div class="row-fluid"> <div class="blog-header__inner dnd-row"> <div class="blog--post__image dnd-section"> <img class="analyst-header-photo" src="https://davidmenninger.isg-research.net/hubfs/_images/_team/Menninger.David%20Pic.Circle.png" style="padding: 10px; "> <br> <h1 class="analyst-header-title">David Menninger's Analyst Perspectives</h1>  </div> </div> </div> </div> <div class="content-wrapper-listing blog-single"> <div class="blog-content-wrapper"> <div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/david-menninger/2016/02/08/pardon-the-interruption-industry-veteran-returns-to-ventana-research">Pardon the Interruption: Industry Veteran Returns to Ventana Research</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">07 February 2016 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_big_data_analytics_18_big_data_technology_in_use.png?width=200&name=vr_big_data_analytics_18_big_data_technology_in_use.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_big_data_analytics_18_big_data_technology_in_use.png?width=100&name=vr_big_data_analytics_18_big_data_technology_in_use.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_big_data_analytics_18_big_data_technology_in_use.png?width=200&name=vr_big_data_analytics_18_big_data_technology_in_use.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_big_data_analytics_18_big_data_technology_in_use.png?width=300&name=vr_big_data_analytics_18_big_data_technology_in_use.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_big_data_analytics_18_big_data_technology_in_use.png?width=400&name=vr_big_data_analytics_18_big_data_technology_in_use.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_big_data_analytics_18_big_data_technology_in_use.png?width=500&name=vr_big_data_analytics_18_big_data_technology_in_use.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_big_data_analytics_18_big_data_technology_in_use.png?width=600&name=vr_big_data_analytics_18_big_data_technology_in_use.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Some followers of Ventana Research may recall my work here several years ago. Here and elsewhere I have spent most of my career in the data and analytics markets matching user requirements with technologies to meet those needs. I’m happy to be returning to Ventana Research to resume investigating ways in which organizations can make the most of their data to improve their business processes; for a first look, please see <u><a href="//davidmenninger.ventanaresearch.com/2016/02/08/research-agenda-using-business-analytics-to-make-the-most-of-data-in-2016/" target="_blank">our 2016 research agenda on Big Data and Information Optimization</a></u>. I relish...</p> </div> <a href="https://davidmenninger.isg-research.net/david-menninger/2016/02/08/pardon-the-interruption-industry-veteran-returns-to-ventana-research"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/big-data">Big Data</a>, <a href="https://davidmenninger.isg-research.net/topic/predictive-analytics">Predictive Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-research.net/topic/internet-of-things">Internet of Things</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/uncategorized">Uncategorized</a>, <a href="https://davidmenninger.isg-research.net/topic/unicorns">Unicorns</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/david-menninger/2012/03/27/research-uncovers-keys-to-using-predictive-analytics">Research Uncovers Keys to Using Predictive Analytics</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">27 March 2012 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span style="font-family: Verdana; font-size: small;">As a technology, predictive analytics has existed for years, but adoption has not been widespread among businesses. In our recent benchmark research on business analytics among more than 2,600 organizations, predictive analytics ranked only 10th among technologies they use to generate analytics, and only one in eight of those companies use it. Predictive analytics has been costly to acquire, and while enterprises in a few vertical industries and specific lines of business have been willing to...</span></p> </div> <a href="https://davidmenninger.isg-research.net/david-menninger/2012/03/27/research-uncovers-keys-to-using-predictive-analytics"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/data-scientist">Data Scientist</a>, <a href="https://davidmenninger.isg-research.net/topic/predictive-analytics">Predictive Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://davidmenninger.isg-research.net/topic/workforce-performance">Workforce Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/david-menninger/2012/03/16/information-management-technology-revolution-and-research-agenda-for-2012">Information Management Technology Revolution and Research Agenda for 2012</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">16 March 2012 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span style="font-size: small;"><span style="font-family: Verdana;">In our definition, information management encompasses the acquisition, organization, dissemination and use of information by organizations to create and enhance business value. Effective information management ensures optimal access, relevance, timeliness, quality and security of this data with the aim to improve organizational performance. This goal is not easily met, especially as organizations acquire ever more data at an ever faster pace. In our <span style="text-decoration: underline;"><a title="business analytics benchmark research" href="//www.ventanaresearch.com/BAM" target="_blank">business analytics benchmark research</a></span> of more...</span></span></p> </div> <a href="https://davidmenninger.isg-research.net/david-menninger/2012/03/16/information-management-technology-revolution-and-research-agenda-for-2012"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/data-quality">Data Quality</a>, <a href="https://davidmenninger.isg-research.net/topic/master-data-management">Master Data Management</a>, <a href="https://davidmenninger.isg-research.net/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://davidmenninger.isg-research.net/topic/complex-event-processing">Complex Event Processing</a>, <a href="https://davidmenninger.isg-research.net/topic/data-governance">Data Governance</a>, <a href="https://davidmenninger.isg-research.net/topic/data-integration">Data Integration</a>, <a href="https://davidmenninger.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://davidmenninger.isg-research.net/topic/information-life-cycle-management">Information Life Cycle Management</a>, <a href="https://davidmenninger.isg-research.net/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/david-menninger/2011/10/07/steve-jobs-leaves-an-indelible-mark-on-business-intelligence">Steve Jobs Leaves an Indelible Mark on Business Intelligence</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">07 October 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>About 30 years ago, perhaps on this very day, I was sitting in front of an Apple II working on a VisiCalc spreadsheet. At the time, I don’t think I even knew who Steve Jobs was. I wasn’t in the software industry yet. I was working for a public accounting firm. The Apple II sat in a corner of the office “typing pool.” For those of you who don’t know what a typing pool was, there was no swimming involved – it was a group of full-time employees with dedicated equipment who did all the typing and...</p> </div> <a href="https://davidmenninger.isg-research.net/david-menninger/2011/10/07/steve-jobs-leaves-an-indelible-mark-on-business-intelligence"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/mobile">Mobile</a>, <a href="https://davidmenninger.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/sustainability">Sustainability</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/business-mobility">Business Mobility</a>, <a href="https://davidmenninger.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://davidmenninger.isg-research.net/topic/financial-performance">Financial Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/governance-risk-compliance-grc">Governance, Risk & Compliance (GRC)</a>, <a href="https://davidmenninger.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://davidmenninger.isg-research.net/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-research.net/topic/location-intelligence">Location Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/visualization">Visualization</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/david-menninger/2011/09/09/splunk-makes-machine-generated-big-data-serve-analytics">Splunk Makes Machine-Generated Big Data Serve Analytics</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">09 September 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span style="font-family: Verdana;"><span style="text-decoration: underline;"><a title="Splunk" href="http://www.splunk.com/" target="_blank">Splunk</a></span> may be one of the biggest software companies you’ve never heard of. I’ve been following the seven-year-old company for over six months now and recently attended its second annual user conference. Splunk focuses on analyzing large volumes of machine-generated data in underlying applications and systems, which includes application and system logs, network traffic, sensor data, click streams and other loosely structured information sources. Many of these “big data” sources are the same...</span></p> </div> <a href="https://davidmenninger.isg-research.net/david-menninger/2011/09/09/splunk-makes-machine-generated-big-data-serve-analytics"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/big-data">Big Data</a>, <a href="https://davidmenninger.isg-research.net/topic/predictive-analytics">Predictive Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://davidmenninger.isg-research.net/topic/machine-data">Machine data</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/2011/05/18/ibm-chooses-hadoop-unity-not-shipping-the-elephant">IBM Chooses Hadoop Unity, Not Shipping the Elephant</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">18 May 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Last week I attended the IBM Big Data Symposium at the Watson Research Center in Yorktown Heights, N.Y. The event was held in the auditorium where the recent Jeopardy shows featuring the computer called Watson took place and which still features the set used for the show – a fitting environment for IBM to put on another sort of “show” involving fast processing of lots of data. The same technology featured prominently in IBM’s big-data message, and the event was an orchestrated presentation more...</p> </div> <a href="https://davidmenninger.isg-research.net/2011/05/18/ibm-chooses-hadoop-unity-not-shipping-the-elephant"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/big-data">Big Data</a>, <a href="https://davidmenninger.isg-research.net/topic/emc">EMC</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://davidmenninger.isg-research.net/topic/cloudera">Cloudera</a>, <a href="https://davidmenninger.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://davidmenninger.isg-research.net/topic/greenplum">Greenplum</a>, <a href="https://davidmenninger.isg-research.net/topic/ibm">IBM</a>, <a href="https://davidmenninger.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://davidmenninger.isg-research.net/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-research.net/topic/infosphere">InfoSphere</a>, <a href="https://davidmenninger.isg-research.net/topic/location-intelligence">Location Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a>, <a href="https://davidmenninger.isg-research.net/topic/stratahadoop">Strata+Hadoop</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/2011/04/29/analytics-for-it-cobblers-children-need-shoes">Analytics for IT: Cobbler’s Children Need Shoes</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">29 April 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>As part of our largest-ever <span style="text-decoration: underline;"><a href="//www.ventanaresearch.com/bam" target="_blank">research study on business analytics</a></span>, which surveyed more than 2,600 organizations covering the maturity and competency of business, IT and vertical industries<span style="text-decoration: underline;">,</span> we looked at how IT is applying analytics to support their own business activities. One of the things we found is that, charged with enabling business units to use information systems as effectively as possible, the IT department, like the shoemaker’s barefoot children in the old tale, typically stands last...</p> </div> <a href="https://davidmenninger.isg-research.net/2011/04/29/analytics-for-it-cobblers-children-need-shoes"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/predictive-analytics">Predictive Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://davidmenninger.isg-research.net/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-research.net/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-research.net/topic/it-analytics">IT Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/it-service-management">IT Service Management</a>, <a href="https://davidmenninger.isg-research.net/topic/itil">ITIL</a>, <a href="https://davidmenninger.isg-research.net/topic/itsm">ITSM</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/2011/04/01/the-information-management-technology-revolution-in-2011">The Information Management Technology Revolution in 2011</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">01 April 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>The information management (IM) technology market is undergoing a revolution similar to the one in the <a href="//davidmenninger.ventanaresearch.com/2011/03/21/the-business-intelligence-technology-revolution-in-2011/">business intelligence (BI) market</a>. We define information management as the acquisition, organization, control and use of information to create and enhance business value. It is a necessary ingredient of successful BI implementations, and while some vendors such as <a href="//davidmenninger.ventanaresearch.com/2010/11/27/ibm-makes-infosphere-information-server-a-force-in-it/">IBM</a>, Information Builders, Pentaho and <a href="//davidmenninger.ventanaresearch.com/2011/03/14/sap-enterprise-information-management-4-0-a-technology-secret/">SAP</a> are in addition integrating their BI and IM offerings, each discipline involves...</p> </div> <a href="https://davidmenninger.isg-research.net/2011/04/01/the-information-management-technology-revolution-in-2011"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/data-quality">Data Quality</a>, <a href="https://davidmenninger.isg-research.net/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-research.net/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-research.net/topic/complex-event-processing">Complex Event Processing</a>, <a href="https://davidmenninger.isg-research.net/topic/data-governance">Data Governance</a>, <a href="https://davidmenninger.isg-research.net/topic/data-integration">Data Integration</a>, <a href="https://davidmenninger.isg-research.net/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-research.net/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/david-menninger/2011/03/21/the-business-intelligence-technology-revolution-in-2011">The Business Intelligence Technology Revolution in 2011</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">20 March 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>The business intelligence (BI) technology market is undergoing a revolution. I’ve been working in this segment for 20 years, and it is and has been an exciting market in which to work, but its dynamic nature can be daunting to organizations trying to evaluate, purchase and deploy BI to improve their business processes. And despite the advances our <a href="//www.ventanaresearch.com/bipm">benchmark research</a> shows high levels of dissatisfaction with and immaturity in BI capabilities within organizations.</p> </div> <a href="https://davidmenninger.isg-research.net/david-menninger/2011/03/21/the-business-intelligence-technology-revolution-in-2011"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/business-mobility">Business Mobility</a>, <a href="https://davidmenninger.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-research.net/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://davidmenninger.isg-research.net/topic/collaboration">Collaboration</a>, <a href="https://davidmenninger.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://davidmenninger.isg-research.net/topic/enterprise-software">Enterprise Software</a>, <a href="https://davidmenninger.isg-research.net/topic/financial-performance">Financial Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-research.net/topic/mobility">Mobility</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://davidmenninger.isg-research.net/david-menninger/2011/03/18/sas-and-its-business-intelligence-information-management-direction">SAS and its Business Intelligence & Information Management Direction</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/isg-software-research"> ISG Software Research </a> on <span class="post-date">17 March 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>I recently attended SAS Institute’s annual analyst conference. My colleague covered the multibillion-dollar company’s <a href="//marksmith.ventanaresearch.com/2011/03/15/sas-institute-the-multi-billion-dollar-business-analytics-supplier-2/">strategy and the event</a>. Now I want to look into some of the details of SAS’s products for business analytics and how they are supported with business intelligence (BI), and information management. Although SAS is not a publicly traded company and therefore is not required to make the financial disclosures that others are, the company revealed numerous financial statistics....</p> </div> <a href="https://davidmenninger.isg-research.net/david-menninger/2011/03/18/sas-and-its-business-intelligence-information-management-direction"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/sas">SAS</a>, <a href="https://davidmenninger.isg-research.net/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-research.net/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-research.net/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-research.net/topic/collaboration">Collaboration</a>, <a href="https://davidmenninger.isg-research.net/topic/enterprise-software">Enterprise Software</a>, <a href="https://davidmenninger.isg-research.net/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-research.net/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-research.net/topic/mobility">Mobility</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <script> // Check active classes var checkClass = function() { if ( $('.fil_item').hasClass('hide') ) { $('.fil_item').removeClass('hide'); 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If you have any issue with an Analyst Perspective, please email them to <a href="mailto:ChiefResearchOfficer@isg-research.net">ChiefResearchOfficer@isg-research.net</a></p> </li> </ul> <a class="btn-secondary" href="https://www.isg-research.net/analyst-perspective-policy">View Policy</a></span>  <div id="hs_cos_wrapper_module_168621267066296" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><style> </style> <h3 style="color: #255a89;">Our Analysts</h3>  <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://davidmenninger.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png" alt="David Menninger" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=50&name=Menninger.David%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=150&name=Menninger.David%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=200&name=Menninger.David%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=250&name=Menninger.David%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=300&name=Menninger.David%20Pic.Circle.png 300w"> <h5 class="analyst_name">David Menninger</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://jefforr.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png" alt="Jeff Orr" width="100" data-constrained="true" caption="false" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=50&name=Orr.Jeff.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=150&name=Orr.Jeff.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=200&name=Orr.Jeff.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=250&name=Orr.Jeff.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=300&name=Orr.Jeff.Circle.png 300w" sizes="(max-width: 100px) 100vw, 100px"> <h5 class="analyst_name">Jeff Orr</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://keithdawson.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png" alt="Keith Dawson" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=50&name=Dawson.Keith%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=150&name=Dawson.Keith%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=200&name=Dawson.Keith%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=250&name=Dawson.Keith%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=300&name=Dawson.Keith%20Pic.Circle.png 300w"> <h5 class="analyst_name">Keith Dawson</h5> </a> </div> <div class="span6" style="text-align:center;"> <a href="https://marksmith.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png" alt="Mark Smith" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=50&name=Smith.Mark%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=150&name=Smith.Mark%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=200&name=Smith.Mark%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=250&name=Smith.Mark%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=300&name=Smith.Mark%20Pic.Circle.png 300w"> <h5 class="analyst_name">Mark Smith</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://mattaslett.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png" alt="Matt Aslett" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=50&name=Aslett.Matt%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=150&name=Aslett.Matt%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=200&name=Aslett.Matt%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=250&name=Aslett.Matt%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=300&name=Aslett.Matt%20Pic.Circle.png 300w"> <h5 class="analyst_name">Matt Aslett</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://matthewbrown.isg-research.net/"> <img class="analyst_img" style="width: 100px;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png" alt="Matthew Brown" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=50&name=profile_vr_matthew_brown_circle_900x900.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=150&name=profile_vr_matthew_brown_circle_900x900.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=200&name=profile_vr_matthew_brown_circle_900x900.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=250&name=profile_vr_matthew_brown_circle_900x900.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=300&name=profile_vr_matthew_brown_circle_900x900.png 300w"> <h5 class="analyst_name">Matthew Brown</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://robertkugel.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png" alt="Robert Kugel" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=50&name=Kugel.Robert%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=150&name=Kugel.Robert%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=200&name=Kugel.Robert%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=250&name=Kugel.Robert%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=300&name=Kugel.Robert%20Pic.Circle.png 300w"> <h5 class="analyst_name">Robert Kugel</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://stephenhurrell.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png" alt="Stephen Hurrell" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=50&name=Hurrell.Stephen%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=150&name=Hurrell.Stephen%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=200&name=Hurrell.Stephen%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=250&name=Hurrell.Stephen%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=300&name=Hurrell.Stephen%20Pic.Circle.png 300w"> <h5 class="analyst_name">Stephen Hurrell</h5> </a> </div> </div>   <div class="row-fluid">  <div style="text-align: center;"> <a href="https://blog.isg-research.net"> <img class="analyst_img" style="width: 100px;" 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dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/08">August 2019 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/07">July 2019 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/06">June 2019 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/05">May 2019 <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/04">April 2019 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/03">March 2019 <span class="filter-link-count" dir="ltr">(9)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/02">February 2019 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/01">January 2019 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/12">December 2018 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/11">November 2018 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/10">October 2018 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/09">September 2018 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/02">February 2018 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/12">December 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/11">November 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/09">September 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/08">August 2017 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/07">July 2017 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/06">June 2017 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/05">May 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/04">April 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/03">March 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/02">February 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/01">January 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/12">December 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/11">November 2016 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/10">October 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/09">September 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/08">August 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/07">July 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/05">May 2016 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/04">April 2016 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/03">March 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/02">February 2016 <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2012/03">March 2012 <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2012/02">February 2012 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2012/01">January 2012 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/12">December 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/11">November 2011 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/10">October 2011 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/09">September 2011 <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/08">August 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/07">July 2011 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/06">June 2011 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/05">May 2011 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/04">April 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/03">March 2011 <span class="filter-link-count" dir="ltr">(7)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/02">February 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/01">January 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2010/12">December 2010 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2010/11">November 2010 <span class="filter-link-count" dir="ltr">(12)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2010/06">June 2010 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> </ul> <a class="filter-expand-link" href="#">see all</a> </div> </div> </span> <span id="hs_cos_wrapper_post_filter" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_post_filter" style="" data-hs-cos-general-type="widget" data-hs-cos-type="post_filter"><div class="block"> <h3>Posts by Topic</h3> <div class="widget-module"> <ul> <li> <a href="https://davidmenninger.isg-research.net/topic/ai">AI <span class="filter-link-count" dir="ltr">(11)</span></a> </li> <li> <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning <span class="filter-link-count" dir="ltr">(95)</span></a> </li> <li> <a href="https://davidmenninger.isg-research.net/topic/alteryx">alteryx <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li> <a href="https://davidmenninger.isg-research.net/topic/alteryx-inspire">Alteryx Inspire <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li> <a href="https://davidmenninger.isg-research.net/topic/analytic-data-platforms">analytic data platforms <span class="filter-link-count" dir="ltr">(1)</span></a> </li> 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dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/external-data-platform">External Data Platform <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/financial-performance">Financial Performance <span class="filter-link-count" dir="ltr">(32)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/financial-performance-management">Financial Performance Management <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/genai">GenAI <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/generative-ai">Generative AI <span class="filter-link-count" dir="ltr">(8)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/governance-risk">Governance & Risk <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/governance-risk-compliance-grc">Governance, Risk & Compliance (GRC) <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/greenplum">Greenplum <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/hadoop">Hadoop <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/hortonworks">Hortonworks <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/hp">HP <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/hpe">HPE <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/human-capital-management">Human Capital Management <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/ibm">IBM <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/ibm-spss">IBM SPSS <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/ibm-watson">IBM Watson <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/in-memory">In-memory <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/in-memory-computing">In-Memory Computing <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/inetsoft">InetSoft <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/infor">Infor <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/infor-birst">Infor Birst <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/informatica">Informatica <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/informatica-hparser">Informatica HParser <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/informatica-world">Informatica World <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/information-applications">Information Applications <span class="filter-link-count" dir="ltr">(15)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/information-builders">Information Builders <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/information-life-cycle-management">Information Life Cycle Management <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/information-management">Information Management <span class="filter-link-count" dir="ltr">(89)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/information-management-im">Information Management (IM) <span class="filter-link-count" dir="ltr">(7)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/information-optimization">Information Optimization <span class="filter-link-count" dir="ltr">(7)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/information-technology">Information Technology <span class="filter-link-count" dir="ltr">(11)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/infosphere">InfoSphere <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/internet-of-things">Internet of Things <span class="filter-link-count" dir="ltr">(26)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/iot">IOT <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/it-analytics">IT Analytics <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/it-performance-management-itpm">IT Performance Management (ITPM) <span class="filter-link-count" dir="ltr">(23)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/it-service-management">IT Service Management <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/itil">ITIL <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/itsm">ITSM <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/kalido">Kalido <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/karmasphere">Karmasphere <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/kognitio">Kognitio <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/kxen">KXEN <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/location-intelligence">Location Intelligence <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/looker">looker <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-data">Machine data <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-learning">Machine Learning <span class="filter-link-count" dir="ltr">(11)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-learning-and-cognitive-computing">Machine Learning and Cognitive Computing <span class="filter-link-count" dir="ltr">(7)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-learning-digital-technology">Machine Learning Digital Technology <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-learning-operations">Machine Learning Operations <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mapr">MapR <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mapreduce">MapReduce <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/marketing">Marketing <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/master-data-management">Master Data Management <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mdx">MDX <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/microsoft">Microsoft <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/microsoft-azure">Microsoft Azure <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/microstrategy">MicroStrategy <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mlops">MLOps <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobile">Mobile <span class="filter-link-count" dir="ltr">(10)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobile-analytics">Mobile Analytics <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobile-business-intelligence">Mobile Business Intelligence <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobile-computing">mobile computing <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobile-intelligence">Mobile Intelligence <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobile-technology">Mobile Technology <span class="filter-link-count" dir="ltr">(18)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobility">Mobility <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/model-building-and-large-language-models">Model Building and Large Language Models <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mpp">MPP <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/natural-language">Natural Language <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/natural-language-processing">natural language processing <span class="filter-link-count" dir="ltr">(46)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/natural-language-query">Natural Language Query <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/netapp">NetApp <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/netezza">Netezza <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/nlg">NLG <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/nlp">NLP <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/nosql">NoSQL <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/odpi">ODPI <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/office-of-finance">Office of Finance <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/olap">OLAP <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/operational-data-plaftforms">operational data plaftforms <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/operational-intelligence">Operational Intelligence <span class="filter-link-count" dir="ltr">(22)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/operations-supply-chain">Operations & Supply Chain 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href="https://davidmenninger.isg-research.net/topic/planning">Planning <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/predictive-analytics">Predictive Analytics <span class="filter-link-count" dir="ltr">(26)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/predictive-planning">Predictive Planning <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/predixion">Predixion <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/process-mining">Process Mining <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/qlik">Qlik <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/qlik-qonnections">Qlik Qonnections <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/qlik-sense">Qlik Sense <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/qlikview">QlikView <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/r">R <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/rd">R&D <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/rdbms">RDBMS <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li 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href="https://davidmenninger.isg-research.net/topic/software-as-a-service">Software as a Service <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/software-evaluation">software evaluation <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/splunk">Splunk <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/spotfire">Spotfire <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/strata-data-conference">Strata Data Conference <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/stratahadoop">Strata+Hadoop <span 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"@context": "http://schema.org", "@type": "BlogPosting", "headline": "Pardon the Interruption: Industry Veteran Returns to Ventana Research", "mainEntityOfPage": "https://davidmenninger.isg-research.net/david-menninger/2016/02/08/pardon-the-interruption-industry-veteran-returns-to-ventana-research", "datePublished": "07/02/2016", "dateModified": "07/02/2016", "articleBody": "Some followers of Ventana Research may recall my work here several years ago. Here and elsewhere I have spent most of my career in the data and analytics markets matching user requirements with technologies to meet those needs. I’m happy to be returning to Ventana Research to resume investigating ways in which organizations can make the most of their data to improve their business processes; for a first look, please see our 2016 research agenda on Big Data and Information Optimization. I relish the opportunity to conduct primary market research in the form of Ventana’s well-known benchmark research and to help end users and vendors apply the information collected in those studies. Much has happened since I was previously part of the Ventana Research team. One major change is the explosive growth in the use and acceptance of big data. For example, when I conducted the first benchmark research on big data, only 22 percent of participants were using Hadoop in production. Our more recent research shows more than 50 percent growth in the number of respondents using Hadoop in production (which is now 37%). In the area of predictive analytics, another research study from my prior tenure identified a skills shortage. This shortage was identified in several ways. More than four out of five (83%) participants indicated that users did not have enough skills training, and more than half (58%) said they didn’t understand the mathematics needed to produce their own analyses. In the interim the numerous university programs have begun to help address this shortage. A Google search shows that New York University, Columbia, Indiana University, Wesleyan, University of Washington, University of Michigan, University of Rochester and University of Texas San Antonio have created data science programs – and this is just page one of the search results. I anticipate that these will be increasingly popular programs as the rise of big data will continue to drive demand for these skills. For the time being, our more recent study on predictive analytics suggests that these skill shortages still exist with very similar responses of 79 percent and 66 percent, respectively. I’ll be continuing to watch these and other analytics issues noted in our 2016 Business Analytics Research Agenda. We have also seen a sea change in the acceptance of open source software in enterprises. I think it is fair to say that open source helped drive the growth in big data with various projects including Cassandra, Hadoop, MongoDB and Spark enabling organizations to experiment with large volumes of data before making significant license purchases to put those systems into production. The open source momentum is further evidenced by some large vendors taking formerly proprietary, “closed source” technologies and making them open source. Perhaps the biggest example is Microsoft making its .NET technology open source. My former employer Pivotal also converted its data management products, in which it had invested more than 10 years of proprietary development, to open source versions. Another notable change is the growth of interest in the Internet of Things (IoT). Many years ago I considered a position with a vendor that helped organizations manage RFID data. Adoption was slow at the time, in part because of the cost of RFID tags but also because of the cost and challenges of collecting and analyzing very large volumes of data. As big data technologies have grown, so too has interest in IoT. Technologies exist today to make processing such large amounts of data possible in the time frames and at costs that make it practical to consider how instrumentation of devices can be used to enhance business performance. We’ll be undertaking specific research on this topic in 2016: See our Big Data and Information Optimization Research Agenda. If he were alive today, Charles Darwin might have noted the emergence of a new species: the Unicorn, which Wikipedia defines as a startup company, often software-based, whose valuation exceeds US$1 billion. You might wonder how this financial trend impacts our research and the advice we provide. The answer is that such valuations have the potential to alter the behavior of the markets we cover. They provide these startup vendors access to funding great enough to change the competitive landscape. Such investments can put pressure on existing vendors to step up their game. In some cases it can also cause consolidation in the market or even cause certain vendors to exit markets, such as Intel did when it decided to get out of the Hadoop distribution market. At Ventana Research we are ready to help end-user organizations evaluate whether the unicorns are ready for prime time and how their existence might impact their existing software vendors. One way in which we help in this process is with our Ventana Research Value Indexes, which provide fact-based assessments of various software products within a variety of market segments. So I hope you’ll pardon the interruption in our conversation. It’s good to be back, and I am looking forward to working with the entire Ventana Research team to provide research and insights that will help guide your use of technology to improve your business decisions and processes. Regards, David Menninger SVP & Research Director", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_big_data_analytics_18_big_data_technology_in_use.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Research Uncovers Keys to Using Predictive Analytics", "mainEntityOfPage": "https://davidmenninger.isg-research.net/david-menninger/2012/03/27/research-uncovers-keys-to-using-predictive-analytics", "datePublished": "27/03/2012", "dateModified": "27/03/2012", "articleBody": "As a technology, predictive analytics has existed for years, but adoption has not been widespread among businesses. In our recent benchmark research on business analytics among more than 2,600 organizations, predictive analytics ranked only 10th among technologies they use to generate analytics, and only one in eight of those companies use it. Predictive analytics has been costly to acquire, and while enterprises in a few vertical industries and specific lines of business have been willing to invest large sums in it, they constitute only a fraction of the organizations that could benefit from them. Ventana Research has just completed a benchmark research project to learn about how the organizations that have adopted predictive analytics are using it and to acquire real-world information about their levels of maturity, trends and best practices. In this post I want to share some of the key findings from our research. As I have noted, varieties of predictive analytics are on the rise. The huge volumes of data that organizations accumulate are driving some of this interest. Our Hadoop research highlights the intersection of this big data and predictive analytics: More than two-thirds (69%) of Hadoop users perform advanced analytics such as data mining. Regardless of the reasons for the rise, our new research confirms the importance of predictive analytics. Participants overwhelmingly reported that these capabilities are important or very important to their organization (86%) and that they plan to deploy more predictive analytics (94%). One reason for the importance assigned to predictive analytics is that most organizations apply it to core functions that produce revenue. Marketing and sales are the most common of those. The top five sources of data tapped for predictive analytics also relate directly to revenue: customer, marketing, product, sales and financial. Although participants are using predictive analytics for important purposes and are generally positive about the experience, they do not minimize its complexities. While now usable by more types of people, this technology still requires special skills to design and deploy, and in half of organizations the users of it don’t have them. Having worked for two different vendors in the predictive analytics space, I personally can testify that the mathematics of it requires special training. Our research bears this out. For example, 58 percent don’t understand the mathematics required. Although not a math major, I had always been analytically oriented, but to get involved in predictive analytics I had to learn new concepts or new ways to apply concepts I knew. Organizations can overcome these issues with training and support. Unfortunately, most are not doing an adequate job in these areas. Not half (44%) said their training in predictive analytics concepts and techniques is adequate, and fewer than one-fourth (24%) provide adequate help desk resources. These are important places to invest because organizations that do an adequate job in these two areas have the highest levels of satisfaction with their use of predictive analytics; 89% of them are satisfied vs. 66% overall. But we note that product training is not the most important type. That also correlated to higher levels of satisfaction, but training in concepts and the application of those concepts to business problems showed stronger correlation. Timeliness of results also has an impact on satisfaction. Organizations that use real-time scoring of records occasionally or regularly are more satisfied than those that use real-time scoring infrequently or not at all. Our research also shows that organizations need to update their models more frequently. Almost four in 10 update their models quarterly or less frequently, and they are less satisfied with their predictive analytics projects than those who update more frequently. In some ways model updates represent the “last mile” of the predictive analytics process. To be fully effective, organizations need to build predictive analytics into ongoing business processes so the results can be used in real time. Using models that aren’t up to date undermines the whole effort. Thanks to our sponsors, IBM and Alpine Data Labs, for helping to make this research available. And thanks to our media sponsors, Information Management, KD Nuggets and TechTarget, for helping in gaining participants and promoting the research and educating the market. I encourage you to explore these results in more detail to help ensure your organization maximizes the value of its predictive analytics efforts. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Information Management Technology Revolution and Research Agenda for 2012", "mainEntityOfPage": "https://davidmenninger.isg-research.net/david-menninger/2012/03/16/information-management-technology-revolution-and-research-agenda-for-2012", "datePublished": "16/03/2012", "dateModified": "16/03/2012", "articleBody": "In our definition, information management encompasses the acquisition, organization, dissemination and use of information by organizations to create and enhance business value. Effective information management ensures optimal access, relevance, timeliness, quality and security of this data with the aim to improve organizational performance. This goal is not easily met, especially as organizations acquire ever more data at an ever faster pace. In our business analytics benchmark research of more than 2,600 organizations, almost half (45%) have to integrate six or more types of data in their analyses. More than two-thirds reported that they spend more time preparing data than analyzing it. To assist in dealing with these sorts of issues and others, we’ve laid out an ambitious information management research agenda for 2012. In recent years the complexity of information management has risen dramatically. The volume of information being processed has increased exponentially and so have the challenges of ensuring consistency and quality and managing governance and the information life cycle. New data types and sources such as comments on social media have emerged and must be integrated into an organization’s information assets. Moreover, in many cases the boundaries between organizations and the outside world with which they interact have become far less distinct, leading to the need for a more expansive understanding of information management. Our Business Data in the Cloud research shows that data is seldom stored in only one repository; the majority of organizations (86%) need to bring together cloud-based data and on-premises data. We will provide new insights on the dynamics of the information management market as we complete research on Information Management Trends. This research will illuminate the priorities organizations place on data quality, master data management and data governance. It will also explore ways in which organizations are incorporating virtualization and replication for broader and faster data access. The growing volumes and sources of data will require data integration that can help facilitate better linkages across IT and into business. We will assess the vendors and products in a Value Index for Data Integration that will determine what suppliers can be best fit for your enterprise. Our research will also help organizations facilitate adoption of and use of big-data technologies. Our recently published Big Data research highlights the role of various technology alternatives for managing data on a large scale. More than 80 percent of organizations utilize more than one technology to tackle their big-data challenges, but organizations lack maturity when incorporating these data sources. Specifically, our research shows that business have not adapted many of their standard processes to deal with big data. We’ll follow up this research by looking at specific vendor capabilities and how they can help extend information management processes to support big data. Data is increasing not only in volume but in velocity as well – the speed with which data is generated and communicated. Technological developments such as smart meters, RFID, sensors and embedded computing devices for environmental monitoring, surveillance and other purposes are creating demand for tools that can derive insights from huge, continuous streams of event data coming into systems in real time. Traditional database systems are geared to manage discrete sets of data for standard BI queries, but event streams from sources such as sensing devices typically are continuous and their analysis requires different kinds of tools that enable users to understand causality, patterns, time relationships and other complex factors. These requirements have led to innovations in complex event processing, event stream processing, event modeling, visualization and analytics. We’ll be exploring how organizations can capitalize on real-time data collection and analysis in our benchmark research on operational intelligence and complex event processing. We will also assess vendors and products in a Value Index to determine the value of vendor offerings in Operational Intelligence to harvest the events from these streams of data. Information management continues to be a strategic business imperative. It can help organizations improve their understanding and use of enterprise information and to establish governance of it. To accomplish these aims they must manage the flow of information throughout the full life cycle of data and provide proper data stewardship to support the business while minimizing risk. We need to better use the information through a simpler means of being able to assemble and deploy it to those in business who might even want to receive it through mobile technologies. This is what we call information applications that can help in timely access to information and should be coupled with an information management discipline. Our research will deliver education and best practices that can help you understand how to reduce the costs, time and risk of delivering these capabilities to your organization. It will be a big year for information management in the forms of technology but also the methods and processes for which to manage and utilize the full value of it within organizations. I look forward to connecting with all of you on LinkedIn or following me on Twitter. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Steve Jobs Leaves an Indelible Mark on Business Intelligence", "mainEntityOfPage": "https://davidmenninger.isg-research.net/david-menninger/2011/10/07/steve-jobs-leaves-an-indelible-mark-on-business-intelligence", "datePublished": "07/10/2011", "dateModified": "07/10/2011", "articleBody": "About 30 years ago, perhaps on this very day, I was sitting in front of an Apple II working on a VisiCalc spreadsheet. At the time, I don’t think I even knew who Steve Jobs was. I wasn’t in the software industry yet. I was working for a public accounting firm. The Apple II sat in a corner of the office “typing pool.” For those of you who don’t know what a typing pool was, there was no swimming involved – it was a group of full-time employees with dedicated equipment who did all the typing and word processing tasks of the office. We all have heard by now that Steve Jobs died this week. When I think about the influence he had on the technology market and business in general, I realize that although I never met the man, his influence has had a huge impact on my career and on all of us who work with business intelligence techniques and tools. The fact that an Apple II was in the office of a public accounting firm in 1981 was a remarkable accomplishment. I probably wouldn’t be in the software industry today if it wasn’t for that Apple II and VisiCalc. Our office used “electronic” spreadsheets to develop planning and allocation models. Now there are hundreds of millions of spreadsheet users whose activities can be traced back to Steve Jobs in some way. You can argue whether the spreadsheet or the Apple II or the combination brought IBM into the personal computer market, but Jobs had an influence here, too. The advent of the PC was the original “self-service BI” movement. Sure, spreadsheets have plenty of problems when applied to business intelligence, as identified in our business analytics benchmark research, but they also have many virtues that we have been trying to capture in other forms of business intelligence software ever since. Jobs and Apple always maintained twin focuses on design and innovation. The design of the physical product was part of the Apple experience, but the design of the user interface was even more important. Our whole way of interacting with information systems, including BI, has been shaped by the graphical user interface (GUI) in part because of the Mac OS. It may not have been the first one, but Apple put a GUI into the hands of end users who saw the possibilities and clamored for more. Ironically, Microsoft Word and Excel first appeared in GUI form on the Mac while the PC versions were still on DOS character-based applications. Spurred by the Mac’s graphical environment, Microsoft took the Windows path that resulted in its own GUI-based operating system. While Microsoft Windows may have enjoyed more commercial success than Mac OS, many still consider Apple’s offering superior in terms of the end-user experience. Regardless of your choice of operating system, BI users wanted and vendors were able to deliver improved GUIs, which now enable users to navigate and visualize large amounts of information more easily than they might have otherwise. And Jobs has left an indelible mark on the mobile computing market. With that same focus on design and innovation, the iPhone and iPad transformed and invigorated the mobile BI market. They fundamentally changed the value of mobile devices, taking them beyond just reading and responding to email. Offered a rich user experience, employees were willing to buy their own devices and bring them along to work. Eventually iPads started showing up in executives’ hands. IT organizations were forced to incorporate these devices into their corporate networks. Users wanted mobile BI, and BI vendors were forced to adapt their products to these new form factors. Our research also shows that 70 percent of organizations either have deployed some type of mobile business intelligence or would like to in the near future. Without stretching much, we can attribute partly to the legacy of Steve Jobs our desire to be connected 24 hours a day and to connect socially via our smartphones and tablets. His influence on these devices made the experience fun and enjoyable. Now collaboration via social media is a regular form of communication. The full impact of these changes is still being borne out in the market, but we are beginning to see an impact on BI. So while Steve Jobs is gone and will be missed, his influence on the BI market will live on. Let’s hope the seeds of innovation that he planted will continue to grow and benefit our lives. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Splunk Makes Machine-Generated Big Data Serve Analytics", "mainEntityOfPage": "https://davidmenninger.isg-research.net/david-menninger/2011/09/09/splunk-makes-machine-generated-big-data-serve-analytics", "datePublished": "09/09/2011", "dateModified": "09/09/2011", "articleBody": "Splunk may be one of the biggest software companies you’ve never heard of. I’ve been following the seven-year-old company for over six months now and recently attended its second annual user conference. Splunk focuses on analyzing large volumes of machine-generated data in underlying applications and systems, which includes application and system logs, network traffic, sensor data, click streams and other loosely structured information sources. Many of these “big data” sources are the same sources analyzed with Hadoop, according to our recently published benchmark research. However, Splunk takes a different approach that focuses on performing simple analyses on this data in real time rather than the batch-based advanced analytics we see as the most common use for Hadoop. Although privately held, Splunk operates much like a public company and appears to be grooming itself for an initial public offering. In its fiscal year ended January 31, 2011, Splunk reported $66 million in revenue and has announced that its goals for FY 2012 include generating $100 million in revenue. With 68% and 70% growth in its first two quarters this year, Splunk appears to be on track to meet this goal. CEO Godfrey Sullivan, formerly CEO of Hyperion, has a successful track record in the business intelligence software space. All these indications suggest a promising future for the company. Data originates from a variety of sources in ever increasing volumes, and organizations are trying to figure out how they can maximize the value of this data. Splunk has rapidly grown based on the simplicity of the tool for IT professionals to adopt and utilize against machine or IT specific data from an individual or department that according to our IT Analytics benchmark finds plenty of demand in IT. As stated above, Splunk focuses on a specific segment of the big-data market: machine-generated data. This type of data originates constantly from many sources throughout an organization and in large quantities. The other common characteristic of machine-generated data is that generally it is less structured than data in typical relational databases. Often the information is captured as logs consisting of text files containing various record lengths and record structures. To effectively utilize this loosely structured information in real time, two challenges must be overcome: loading the data quickly and easily navigating through and analyzing the information once it is loaded. Splunk tackles the first challenge by loading the information in its raw form. No preprocessing is necessary, therefore no delay is introduced and no data is “lost.” Retaining all the raw data has business value as well. If you later decide that you want to investigate some new piece of information that previously you didn’t think was important, it will be available for analysis. A search-based mechanism provides the solution to the second challenge. Our information applications research shows the importance of search, which ranked third on the list of very important analysis capabilities overall, and for end users specifically it topped the list of very important capabilities (46%), ahead of navigating to and retrieving information. Search based access to analytics has been a large driver in growth and was highlighted by my colleague in 2009. Search overcomes the issues created by the lack of “structure” in the machine-generated data. In reality the data has plenty of structure – users search for strings representing occurrences of certain types of events. Splunk supplements the query mechanism with analytical functions that can be used to create aggregates, time-period comparisons and other common analyses. In addition, queries can be saved for reuse and as the basis of reports, dashboards and alerts. I heard anecdotal proof of the value of search at the Splunk user conference from two undergraduate students who, as part of their summer internship, had learned the Splunk query techniques quickly and implemented reports and analyses for monitoring the systems of a major financial services software company. Architecturally, Splunk employs massively parallel processing to spread the data and processing across a number of individual servers. At query time, a proprietary MapReduce mechanism – one not based on Hadoop – gathers the data from the individual nodes to satisfy the user’s request. Users do not need to know about the MapReduce mechanism. The translation of the query to the appropriate execution strategy is done automatically. However, as with any distributed data system, some knowledge of how the data gets distributed across the nodes can be helpful in identifying performance bottlenecks and tuning certain slowly running queries. The currently released version, Splunk 4.2 was introduced earlier in 2011 and includes real-time alerting on streams of data. It also includes a new agent-based data collection mechanism, called a universal forwarder, that makes the task easier and provides more reliability when collecting data from multiple endpoints or devices. Splunk separates the workload between indexers that perform the data loading and search heads that execute the queries. Version 4.2 introduced search-head pooling for load balancing so searches can be directed to anyone of the search heads; it also provides high availability among the search processes. At the conference, Splunk introduced version 4.3 and made the beta version available to registered users. One of the more popular demonstrations was Splunk 4.3 running as a non-Flash application on the iPad. The company also made a number of announcements of specific applications and extensions of the product. Splunk Storm provides visibility and operational analytics of cloud-based applications. Splunk App for Citrix XenDesktop and Splunk App for VMWare provide visibility into virtualized and private cloud environments. The company also introduced a software development kit (SDK) for the Python programming language, which is open source and available at github. The Splunk product is not perfect, of course. Continued investment in the user interface is needed to make it easier to use. Currently users have to learn the Splunk syntax – I was introduced to those internals to show that this is easy – and a graphical query interface also would make the product more widely usable. When I probed about high availability, it became clear that you can use the Splunk tools to load dual systems to have a standby system in case of failure, but that’s not done automatically. But the company representatives were open about its shortcomings with both me and its customers, which was refreshing. Nearly every organization has some form of machine data. Splunk says that more than 2,900 enterprises have found a reason to purchase its products. The company’s mission is now to raise its visibility and broaden its applicability. Splunk provides a free, limited-capability version of its product so you can try it for yourself and see if it applies to your needs. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "IBM Chooses Hadoop Unity, Not Shipping the Elephant", "mainEntityOfPage": "https://davidmenninger.isg-research.net/2011/05/18/ibm-chooses-hadoop-unity-not-shipping-the-elephant", "datePublished": "18/05/2011", "dateModified": "18/05/2011", "articleBody": "Last week I attended the IBM Big Data Symposium at the Watson Research Center in Yorktown Heights, N.Y. The event was held in the auditorium where the recent Jeopardy shows featuring the computer called Watson took place and which still features the set used for the show – a fitting environment for IBM to put on another sort of “show” involving fast processing of lots of data. The same technology featured prominently in IBM’s big-data message, and the event was an orchestrated presentation more like a TV show than a news conference. Although it announced very little news at the event, IBM did make one very important statement: The company will not produce its own distribution of Hadoop, the open source distributed computing technology that enables organizations to process very large amounts of data quickly. Instead it will rely on and throw its weight behind the Apache Hadoop project – a stark contrast to EMC’s decision to do exactly that, announced earlier in the week. As an indication of IBM’s approach, Anant Jhingran, vice president and CTO for information management, commented, “We have got to avoid forking. It’s a death knell for emerging capabilities.” The event brought together organizations presenting interesting and diverse use cases ranging from traditional big-data stories from Web businesses such as Yahoo to less well known scenarios such as informatics in life sciences and healthcare, by Illumina and the University of Ontario Institute of Technology (UOIT), respectively, low-latency financial services by eZly and customer demographic data by Axciom. Eric Baldeschwieler, vice president of Hadoop development at Yahoo, shared some impressive statistics about its Hadoop usage, one of the largest in the world with over 40,000 servers. Yahoo manages 170 petabytes of data with Hadoop and runs more than 5 million Hadoop jobs every month. The models it uses to help prevent spam and others that do ad-targeting are in some cases retrained every five minutes to ensure they are based on up-to-date content. As a point of reference CPU utilization on Yahoo’s Hadoop computing resources averages greater than 30% and at its best is greater than 80%. It appears from these figures that the Hadoop clusters are configured with enough spare capacity to handle spikes in demand. During the discussions, I detected a bit of a debate about who is the driving force behind Hadoop. According to Baldeschwieler, Yahoo has contributed 70% of the Apache Hadoop project code, but on April 12, Cloudera claimed in a press release, “Cloudera leads or is among the top three code contributors on the most important Apache Hadoop and Hadoop-related projects in the world, including Hadoop, HDFS, MapReduce, HBase, Zookeeper, Oozie, Hive, Sqoop, Flume, and Hue, among others.” Perhaps Yahoo wants to reestablish its credentials as it mulls whether to spin out its Hadoop software unit. If such a spinoff were to occur, it could further fracture the Hadoop market. I found it interesting that the customers IBM brought to the event, while having interesting use cases, were not necessarily leveraging IBM products in their applications. This fact led me to the initial conclusion that the event was more of a show than a news conference. Reflecting further on IBM’s stated direction of supporting the Apache Hadoop distribution, I wondered what IBM Hadoop-related products they would use. IBM will be announcing version 1.1 of InfoSphere BigInsights in both a free basic edition and an enterprise edition. The product includes Big Sheets, which can integrate large amounts of unstructured Web data. InfoSphere Streams 2.0, announced in April, adds Netezza TwinFin, Microsoft SQLServer and MySQL support to other SQL sources already supported. But this event was not about those products. It was about IBM’s presence in and knowledge of the big-data marketplace. Executives did say that the IBM product portfolio will be extended “in all the places you would expect” to support big data but offered few specifics. IBM emphasized the combination of streaming data, via InfoSphere Streams, and big data more than other big-data vendors do. The company painted a context of “three V’s” (volume, velocity and variety) of data, which attendees, Twitter followers and eventually the IBM presenters expanded to include a fourth V, validity. To illustrate the potential value of combining streaming data and big data, Dr. Carolyn McGregor, chair in health informatics at UOIT, shared how the institute is literally saving lives in neonatal intensive care units by monitoring and analyzing neonatal data in real time. Rob Thomas, IBM vice president of business development for information management explained the role of partners in the IBM big data ecosystem. As stated above, IBM will rely on Apache Hadoop as the foundation of its work, but will partner with vendors further up the stack. Datameer, Digital Resaoning, and Karmasphere all participated in the event as examples of the types of partnerships IBM will seek. IBM has already demonstrated, via Watson, that it knows how to deal with large-scale data and Hadoop, but to date, if you want those same capabilities from IBM, it will have to come mostly in the form of services. The event made it clear that IBM backs the Apache Hadoop effort but not in the form of new products. In effect, IBM used its bully pulpit (not to mention its size and presence in the market) to discourage others from fragmenting the market. The announcements may also have been intended to buy time for further product developments. I look for more definition from IBM on its product roadmap. If it wants to remain competitive in the big-data market, IBM needs to articulate how its products will interact with and support Hadoop. In my soon to be released Hadoop and Information Management benchmark research that I am completing will provide some facts on whether or not IBM is making the right bet on Hadoop. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Analytics for IT: Cobbler’s Children Need Shoes", "mainEntityOfPage": "https://davidmenninger.isg-research.net/2011/04/29/analytics-for-it-cobblers-children-need-shoes", "datePublished": "29/04/2011", "dateModified": "29/04/2011", "articleBody": "As part of our largest-ever research study on business analytics, which surveyed more than 2,600 organizations covering the maturity and competency of business, IT and vertical industries, we looked at how IT is applying analytics to support their own business activities. One of the things we found is that, charged with enabling business units to use information systems as effectively as possible, the IT department, like the shoemaker’s barefoot children in the old tale, typically stands last in line for resources to manage its own performance. In trying to understand and tune the collection of networking and operating systems, middleware and applications an enterprise needs to operate, IT professionals usually have to make do with small sets of historical data stored in spreadsheets and data warehouses and marts that are not as well managed as the systems they maintain to support the business. In most cases IT cannot apply the same level of analytics to its own operations that it provides to business units. This also has effects beyond IT itself: To the extent that the result is subpar performance of its core information systems, the business will suffer. To break out of this frustrating cycle, IT needs to make the rest of the organization aware of the role it actually performs, of course, and it needs metrics and measurements, which require analytics to standardize and routinely generate them. IT needs to be able to analyze both historical and real-time events involving data and processes so managers can determine the right level of automation and efficiency to demand from the technology. And IT needs the capability delivered by predictive analytics to anticipate situations and outcomes so it can prepare properly for them. In short, the CIO and IT staff need to manage their portfolio as a business asset, not merely a collection of technologies. Metrics about its own operations and systems also enable IT to determine priorities for improvement. To fully understand the state of their existing investments and processes, IT organizations should not just measure them but analyze them to develop insights on future outcomes of their systems. This more sophisticated approach to analytics can help IT determine where to focus resources and what to do with legacy systems. Knowing this, it is possible to prioritize precious budget dollars and justify IT investments more convincingly. Our research found that IT’s concerns currently center on cost and operational efficiency. The most important financial metrics are return on investment, cost per project, budget utilization and adherence to budget. The most important process metrics address timeliness in IT’s core function of service to the business: delivery of projects on time, speed of technology implementation and help desk response time. In our research, which we presented in this webinar on IT analytics, of the participants’ perceptions of which metrics are most important for executives and managers, two loomed large: business user satisfaction and compliance with service level agreements (SLAs). The executives themselves rated the two metrics nearly equal in importance, but their management reports (vice presidents) by a slight margin most often named adherence to governance and risk management requirements rather than either of those. These responses suggest that people may work somewhat at cross-purposes in pursuing IT analytics. The research also finds strong suggestions that organizations ought to involve more people in the process of establishing requirements for defining analytics. Research participants asserted overwhelmingly that they and the head of their business unit are involved in establishing requirements important to their jobs, but percentages drop for heads of other business units and business analysts in other business units. This disparity takes on more weight when we recall that business user satisfaction and SLA compliance are important metrics for leaders. For analytics to deliver value, they must be available to those who need them; the research shows that this is an issue for many organizations. No more than half have analytics generally available to address any of seven major IT management tasks, and only for budget analysis are analytics completely available in even one-fourth of organizations. In a related finding, more than half said it is very important to make it simpler to provide analytics and metrics; less than 10 percent said that is only somewhat important or not important. As well, over a third said they can significantly improve their use of analytics and performance indicators, and over a third are not satisfied with the process currently used to create analytics. The process of applying analytics also impacts IT’s effectiveness. The IT Analytics benchmark research found that users in nearly two-thirds of all organizations spend most of their time in unproductive chores that precede analyzing their data: preparing it for analysis, reviewing it for quality and consistency and waiting for it. And before that, issues in collecting the data raise another roadblock. In more than half of organizations, doing that is very difficult or a challenge that impedes creating metrics and performance indicators. These functional barriers also can get in the way of analysts performing important tasks. Among capabilities they need in order to work effectively with analytics and metrics, 42 percent said access to source data is the most important, and at least one-third identified as most important the abilities to search for existing data and analytics, to take action based on analytics and to design and maintain both business models and metrics for analytics. Applying predictive analytics to project future outcomes, a hallmark of advanced maturity in the use of IT analytics, was cited by 31 percent. IT professionals need appropriate tools to facilitate these and other analytics-related activities. In more than half of these organizations, business intelligence technologies for query, reporting, analysis are the most important of these tools. Yet even in this technologically astute environment, desktop spreadsheets are often used to generate analytics and are an important information source for building IT. But spreadsheets require manual effort to populate the data and are prone to error, and thus are not appropriate for collaborative and enterprise-wide activities. We think their widespread use is a factor in half of organizations being only somewhat satisfied or not satisfied with their organization’s current technology for creating and applying analytics. As part of our benchmark research methodology, Ventana Research has developed a model for assessing maturity that classifies organizations at four maturity levels (from bottom to top, Tactical, Advanced, Strategic and Innovative) in each of four categories: People, Process, Information and Technology. With respect to their use of and plans for IT analytics, our Maturity Index analysis found only 15 percent whose responses place them at the highest Innovative level of maturity. One important finding reflecting on organizations’ maturity is that two-thirds said the data used in preparing metrics and performance indicators is only somewhat accurate or somewhat inaccurate. As well, it takes 35 percent of organizations more than one week to provide updated metrics and performance indicators to people and nearly as many up to a week to provide them. It is a positive sign that improvements, if made, will be done most often to improve business processes or decision-making rather than for operational efficiency and cost savings. The first two motivations are more likely to produce better business results. Similarly, maximizing IT effectiveness and improving the value of IT to business managers are more important than issues involving resources, costs and budget. However, these opinions come from organizations that plan to change the way they generate and apply analytics in the next 12 to 18 months, and they comprise only 28 percent of the total; another 36 percent said changes are needed but are not currently a priority. The primary barriers to such an initiative are both fiscal (lack of resources and budget) and perceptual (lack of awareness and a sense that the business case is not strong enough). Recognizing a problem but not being willing or able to remedy it is another sign of immaturity. To maximize its value, IT should use analytics and metrics to help set its own goals and objectives and to ensure they serve the business strategies of the organization. This innovative path is embracing IT performance management. Few organizations have taken the necessary steps to actually manage performance and align, optimize and understand the range of their IT processes and resources. We believe, and this benchmark research confirms, that it is time for them to take those steps, supported by executive management in providing resources. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "The Information Management Technology Revolution in 2011", "mainEntityOfPage": "https://davidmenninger.isg-research.net/2011/04/01/the-information-management-technology-revolution-in-2011", "datePublished": "01/04/2011", "dateModified": "01/04/2011", "articleBody": "The information management (IM) technology market is undergoing a revolution similar to the one in the business intelligence (BI) market. We define information management as the acquisition, organization, control and use of information to create and enhance business value. It is a necessary ingredient of successful BI implementations, and while some vendors such as IBM, Information Builders, Pentaho and SAP are in addition integrating their BI and IM offerings, each discipline involves different aspects of the use of information and will require it sometimes integrated and sometimes separate. Some might consider information management as the “plumbing” behind BI. They take it for granted and only notice when it is missing. We have a more holistic view. Our recent benchmark research on business analytics shows that, for example, organizations struggle to collect all the data they need, with two-thirds of them stating they spend more time in data related activities than analytic ones. Three key issues are driving our information research agenda in 2011: 1) Combining all the sources and types of data into an integrated information architecture. 2) Enabling organizations to manage and analyze larger volumes of information. 3) Providing accessibility to information throughout the organization. We’ll be updating our information management benchmark research this year to see how these central issues are impacting IM overall. In addition we will focus on five technology innovations my colleague has identified as the business technology revolution in 2011: cloud computing, mobile technologies, social media, analytics of more types over more data and collaboration. Let me flesh out each of these a bit as they impact the evolution of IM. As I pointed out in “Clouds Are Raining Corporate Data,” cloud computing is having an increasingly large influence over the IT landscape. It’s likely that, whether you realize it or not, corporate data exists and/or is migrating outside the walls of your organization. Cloud-based applications and services raise information management challenges that don’t necessarily exist in on-premises deployments. We’re investigating these issues now in our Business Data in the Cloud benchmark research program and where many new providers dealing with cloud data like Dell Boomi, Jitterbit and Snapdata play into the existing landscape of IBM, Informatica, iWay Software, Oracle, Pervasive and Syncsort to name just a few. Mobile technologies are enabling organizations to deliver information to users when and where they need it. They are one of the forces driving cloud adoption as organizations look to make it easier to deliver applications to users regardless of their location. Mobile applications also are consuming and producing more location-related information and creating a need to manage this kind of data. In the world of information management, social media has created entirely new challenges. Most social media data is unstructured text and is forcing organizations to embrace text analytics to deal with it, in many cases for the first time. The volumes of social media data and the speed with which it should be collected and analyzed also present new challenges. From an IM perspective, organizations must learn how to solve these challenges while enforcing appropriate data quality, data governance and life-cycle management policies. Analytics present an additional set of IM challenges. The necessity of managing more data and different types of data has led to the adoption of large-scale technologies such as Hadoop. In research that is under way now we are researching the various ways of dealing with these huge data volumes and the role of Hadoop in that process. Predictive analytics also create IM challenges. Sampling, which is a key to producing unbiased predictive models, may or may not become less critical as database analytics grow in popularity. The models and the scores that such analytics produce are another form of data that must be managed and retained, often for compliance and auditing purposes. We’ll be studying these issues as part of predictive analytics benchmark research that will commence in the first part of 2011. Collaboration provides a means to communicate and extend the processes of IM. It creates a new channel not only for delivery of information but also for input into the delivery process. Using collaboration tools such as Twitter, Chatter or Tibbr can help organizations use data and related information by involving more people. This wider audience collectively contains more knowledge about the underlying data and can also comment on its quality, which ultimately will lead to better data and more trust in it. Collaboration tools also provide a mechanism to link the workflows of information management with the constituents involved in the process. Information management continues to evolve and grow, somewhat to my surprise as indicated in my recent assessment of Informatica. These changes present challenges for IT groups and lines of business alike. With our IM research agenda, we hope to provide useful information to both functions and help you navigate together through this changing landscape and achieve the goal of creating and enhancing business value. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "The Business Intelligence Technology Revolution in 2011", "mainEntityOfPage": "https://davidmenninger.isg-research.net/david-menninger/2011/03/21/the-business-intelligence-technology-revolution-in-2011", "datePublished": "20/03/2011", "dateModified": "20/03/2011", "articleBody": "The business intelligence (BI) technology market is undergoing a revolution. I’ve been working in this segment for 20 years, and it is and has been an exciting market in which to work, but its dynamic nature can be daunting to organizations trying to evaluate, purchase and deploy BI to improve their business processes. And despite the advances our benchmark research shows high levels of dissatisfaction with and immaturity in BI capabilities within organizations. Challenges remain to spread adoption of BI among a wider audience and improve its use in organizations. We have recently seen progress in integrating information management and analytics into a single framework, but more work remains. The use of collaboration will help improve dialogue and delivery of information to business users. Organizations can also adopt and support mobile BI technologies to enhance productivity and broaden the reach of BI. Technology exists today to apply analytics to all information regardless of volume, data type and origin. However, organizations still struggle to evaluate alternatives for supporting large data sets including location data, event data and machine-generated data, all of which can contribute to more accurate analyses of their business processes. Also as the proportion and volume of unstructured data grow, users will need to incorporate text analytics to complement structured data analysis. On top of these challenges businesses now operate at Internet speeds and must analyze data and events as they are created or miss fleeting market opportunities. Organizations must develop their analytical capabilities further not just to provide data but to optimize business decisions. To enhance decision-making and improve business outcomes, they must move beyond historical analysis to look forward through planning, forecasting and predictive analysis. And the dramatic rise in popularity of social media creates another source of information to incorporate in the decision-making process and another channel for involving larger groups in feedback processes. We see five underlying technology innovations impacting BI and creating the aforementioned revolution: cloud computing, mobile technologies, social media, analytics of more types over more data, and collaboration. My colleague has identified these five areas as the business technology revolution in 2011, and all are directly relevant to BI. As I’ve previously pointed out in “Clouds are Raining Corporate Data”, cloud-based BI systems are rising in popularity. So are other types of cloud applications, which means that more and more of the data organizations need to analyze will reside in the cloud. I’ll be examining the issues of business data in the cloud in a benchmark research program that is just about to get under way. Mobile technologies are invading the enterprise through employees. As mobile devices have developed more capabilities and larger form factors appear in tablets, business users on the go are demanding access to BI wherever they may be. Some software vendors and innovative enterprises have recognized these devices as vehicles to enable front-line BI and decision-making capabilities. More organizations are supporting their business users and realizing benefits of both broader BI adoption and enhanced productivity of their workforce. Social media has created several new challenges for businesses and their use of BI. First, this rich source of information can help companies understand customers and prospects, their characteristics, their opinions and their experiences in interacting with the organization. But analyzing unstructured social media content is new to most organizations. Second, social media can also play a role in collaborating on BI-aided decision-making processes (discussed below). Third, social media is a source of information and opinions about the BI products and services organizations may be evaluating. Finally, the combination of social media and mobile technologies is increasing demand for real-time data and instant analysis of it. Collaboration technologies, as applied to BI, are not the same as social media. Social media such as Twitter, Chatter or Tibbr may be used as part of a social process, but collaboration is more than just a conversation. It includes workflow and approval processes as well as tracking communication associated with BI decision-making. Social media can be the delivery vehicle for some of the information and conversation tracking, but it is not sufficient on its own. Innovative organizations recognize the processes involved in BI are as important as the technology and take steps to provide collaborative support to their BI activities. The rise of social media has helped raise awareness of collaboration in general, but many organizations are still confused about how to apply collaboration to the BI process. At the core of BI, analytics have evolved beyond simple historical analysis. More advanced analytic techniques have been available for decades but are still not widely embraced. For example, our recent analytics research shows that only 25% of organizations are using planning and forecasting in their BI applications. However, in business areas such as finance, planning with what-if and scenario modeling has been common for years, in part because the volumes of data were smaller and more easily managed. In other specific business functions such as fraud detection, predictive analytics have played a significant role for years despite their cost and complexity because of the magnitude of the savings that could be achieved. With these business areas paving the way and with the advent of information management technologies that can marry larger volumes of data with more powerful analytics, organizations can now deploy these capabilities across a much wider range of business problems. I’ll be examining the role of advanced analytics and the obstacles still facing organizations as they try to deploy these capabilities. In short, while the challenges are great, so are the opportunities. It’s an exciting time in the BI market. As you assess how the business technology revolution affects your BI efforts, please check back here for updated research that can help your organization mature in its use of BI. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "SAS and its Business Intelligence & Information Management Direction", "mainEntityOfPage": "https://davidmenninger.isg-research.net/david-menninger/2011/03/18/sas-and-its-business-intelligence-information-management-direction", "datePublished": "17/03/2011", "dateModified": "17/03/2011", "articleBody": "I recently attended SAS Institute’s annual analyst conference. My colleague covered the multibillion-dollar company’s strategy and the event. Now I want to look into some of the details of SAS’s products for business analytics and how they are supported with business intelligence (BI), and information management. Although SAS is not a publicly traded company and therefore is not required to make the financial disclosures that others are, the company revealed numerous financial statistics. Business intelligence represents over $200 million in license revenue to SAS. That’s a significant figure, larger than publicly traded BI vendors QlikTech (NASDAQ: QLIK) and Actuate (NASDAQ: BIRT) have and smaller than but still in the same order of magnitude as MicroStrategy (NASDAQ: MSTR) and Information Builders. These figures are consistent with results in our benchmark research on business intelligence and performance management: 18% of our research respondents reported using SAS products, which places it in the middle of the pack. SAS has a broad portfolio of BI products including query, reporting, OLAP, visualization and dashboarding. The existing product line lags behind competitive offerings’ collaboration and mobile capabilities, but SAS has plans to address these areas. An upcoming release, planned for later in 2011, will focus on visualization, some in-memory capabilities, expanded collaboration and mobile deployments. SAS has a history in the visualization space with its JMP product. The new release will bring more visualization along with in-memory technology to the core BI product. The visualization capabilities will be delivered in both iPad and Flash versions. My colleague highlighted collaboration as one of five technologies creating a revolution in business in 2011. On the collaboration front, SAS provided integration with Microsoft Outlook last summer and will be expanding those capabilities. I am a fan of Outlook integration. The product may not be as sexy as Salesforce Chatter or other social media channels, but a collaboration channel must have critical mass to be successful. That is, if the people you need to interact with aren’t present on that channel, your communications won’t reach the intended recipients. Integration with Outlook solves that problem because everyone in the enterprise uses e-mail and it is the dominant client software. Sure, I’d like to see a roadmap that includes other collaboration channels, but Outlook is the logical starting point and can be a bridge until those other channels are more widely adopted. Users should be aware that many SAS applications were built before its BI stack was available and are still based on separate components. Newer applications such as Customer Intelligence are based on the BI stack, but older applications are migrating to the BI stack only over time. This obviously impacts integration among parts of the product line. But since many applications are not based on the BI stack, there is less pull-through from sales of those applications, and this suggests that the BI products are succeeding on their own. When it comes to information management, SAS let’s its wholly owned software business handle the development of its products and to the marketing and sales activities. DataFlux, acquired by SAS more than 10 years ago, maintains a separate identity and a separate product line from SAS Data Integration, although the underlying components and metadata, rules and transformations can be shared and process flows can be orchestrated between the two lines. DataFlux, with over 2,300 customers, provides data integration, data quality and master data management capabilities. In 2011 it will be moving into complex event processing for operational intelligence. See our benchmark research on the subject here. While the SAS and DataFlux information management products can deal with cloud-based data, they do not yet offer a software-as-a-service versions of their products, which some other vendors do. SAS also needs to provide more integration between its BI products and the information management products. For instance, data lineage and glossary information cannot be surfaced through the BI products today, although SAS can provide impact analysis of where information is used in the BI products. Business analytics at SAS is a separate category from BI. In it SAS includes statistics, forecasting, predictive analytics and text analytics. Our recent BI and performance management benchmark research shows that less than one-quarter of respondents use predictive analytics. However, in our newly completed benchmark research on business analytics 80% of organizations said that it is important or very important to apply predictive analytics to predict future outcomes, so we expect usage to grow. SAS has a long history in the analytics space and a well-developed product line, but it is still extending its algorithms. In 2011 SAS will be focusing on new algorithms for high-frequency data and more powerful optimization techniques. Part of the development centers around high-performance computing techniques that distribute processing across multiple servers to handle large volumes of data quickly. These high-performance techniques will be delivered as an analytic appliance. SAS also plans to provide operational analytics through workflow and business rules. In all the talk of high-performance computing, SAS said little about Hadoop. I expect to hear more from SAS on this topic, but the plans are still in the formative stages. (For discussion of what other organizations are doing with Hadoop, see my previous post “Living in the Era of Hadoop and Large-Scale Data”. SAS is also working on enterprise search capabilities, which we believe are important as discussed here So while most of SAS’s business derives from applications, there is a robust tools business for BI, analytics and information management. Whether you are an SAS customer or not, I hope this recap of what’s going on at SAS helps you understand some of the ways in which analytics and BI are becoming more intertwined. 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David Menninger's Analyst Perspectives | IT Performance Management (ITPM)