David Menninger's Analyst Perspectives

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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 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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/stream-and-event-processing-require-real-time-analytics">Stream and Event Processing Require Real-Time 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">25 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Stream_and_Event_Processing_Require_Real-Time_Analytics.png?width=200&name=Stream_and_Event_Processing_Require_Real-Time_Analytics.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Stream_and_Event_Processing_Require_Real-Time_Analytics.png?width=100&name=Stream_and_Event_Processing_Require_Real-Time_Analytics.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Stream_and_Event_Processing_Require_Real-Time_Analytics.png?width=200&name=Stream_and_Event_Processing_Require_Real-Time_Analytics.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Stream_and_Event_Processing_Require_Real-Time_Analytics.png?width=300&name=Stream_and_Event_Processing_Require_Real-Time_Analytics.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Stream_and_Event_Processing_Require_Real-Time_Analytics.png?width=400&name=Stream_and_Event_Processing_Require_Real-Time_Analytics.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Stream_and_Event_Processing_Require_Real-Time_Analytics.png?width=500&name=Stream_and_Event_Processing_Require_Real-Time_Analytics.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Stream_and_Event_Processing_Require_Real-Time_Analytics.png?width=600&name=Stream_and_Event_Processing_Require_Real-Time_Analytics.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>In my past perspectives, I’ve written about the evolution from <a href="https://davidmenninger.ventanaresearch.com/historical-databases-becoming-a-thing-of-the-past" rel="noopener" target="_blank">data at rest to data in motion</a> and the fact that <a href="https://davidmenninger.ventanaresearch.com/dont-rely-on-dashboards-for-real-time-analytics" rel="noopener" target="_blank">you can’t rely on dashboards for real-time analytics</a>. Organizations are becoming more and more event-driven and operating based on streaming data. As well, analytics are becoming more and more intertwined with operations. More than one-fifth of organizations (22%) describe their analytics workloads as real time in our Data and Analytics Benchmark Research and nearly half (47%) of...</p> </div> <a href="https://davidmenninger.isg-research.net/stream-and-event-processing-require-real-time-analytics"><span class="readmore"> Read More </span></a><br><br> Topics: <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/data">Data</a>, <a href="https://davidmenninger.isg-research.net/topic/digital-technology">Digital Technology</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-analytics">Streaming Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics-data">Analytics & Data</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-data-events">Streaming Data & Events</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/the-buyers-guide-for-mobile-analytics-classifies-and-rates-vendors">The Buyers Guide for Mobile Analytics Classifies and Rates Vendors</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">17 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png?width=100&name=The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png?width=300&name=The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png?width=400&name=The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png?width=500&name=The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png?width=600&name=The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The </span><a href="https://www.ventanaresearch.com/buyers_guide/analytics/mobile_analytics_2023"><span data-contrast="none">Ventana Research 2023 Mobile Analytics Buyers Guide</span></a><span data-contrast="auto"> is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics vendors supporting the spectrum...</span></p> </div> <a href="https://davidmenninger.isg-research.net/the-buyers-guide-for-mobile-analytics-classifies-and-rates-vendors"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics-data">Analytics & Data</a>, <a href="https://davidmenninger.isg-research.net/topic/mobile-analytics">Mobile Analytics</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/mobile-analytics-buyers-guide-market-observations">Mobile Analytics Buyers Guide: Market Observations</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 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Mobile_Analytics_Buyers_Guide_Market_Observations.png?width=200&name=Mobile_Analytics_Buyers_Guide_Market_Observations.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Mobile_Analytics_Buyers_Guide_Market_Observations.png?width=100&name=Mobile_Analytics_Buyers_Guide_Market_Observations.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Mobile_Analytics_Buyers_Guide_Market_Observations.png?width=200&name=Mobile_Analytics_Buyers_Guide_Market_Observations.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Mobile_Analytics_Buyers_Guide_Market_Observations.png?width=300&name=Mobile_Analytics_Buyers_Guide_Market_Observations.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Mobile_Analytics_Buyers_Guide_Market_Observations.png?width=400&name=Mobile_Analytics_Buyers_Guide_Market_Observations.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Mobile_Analytics_Buyers_Guide_Market_Observations.png?width=500&name=Mobile_Analytics_Buyers_Guide_Market_Observations.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Mobile_Analytics_Buyers_Guide_Market_Observations.png?width=600&name=Mobile_Analytics_Buyers_Guide_Market_Observations.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">The 2023 Ventana Research Buyers Guide for Mobile Analytics research enables me to provide observations about how the market has advanced. </span></p> </div> <a href="https://davidmenninger.isg-research.net/mobile-analytics-buyers-guide-market-observations"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics-data">Analytics & Data</a>, <a href="https://davidmenninger.isg-research.net/topic/mobile-analytics">Mobile Analytics</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/the-buyers-guide-for-collaborative-analytics-classifies-and-rates-vendors">The Buyers Guide for Collaborative Analytics Classifies and Rates Vendors</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">13 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png?width=100&name=The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png?width=300&name=The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png?width=400&name=The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png?width=500&name=The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png?width=600&name=The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The </span><a href="https://www.ventanaresearch.com/buyers_guide/analytics/collaborative_analytics_2023"><span data-contrast="none">Ventana Research 2023 Collaborative Analytics Buyers Guide</span></a><span data-contrast="auto"> is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics vendors supporting the...</span></p> </div> <a href="https://davidmenninger.isg-research.net/the-buyers-guide-for-collaborative-analytics-classifies-and-rates-vendors"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics-data">Analytics & Data</a>, <a href="https://davidmenninger.isg-research.net/topic/collaborative-analytics">Collaborative Analytics</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/collaborative-analytics-buyers-guide-market-observations">Collaborative Analytics Buyers Guide: Market Observations</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">12 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Collaborative_Analytics_Buyers_Guide_Market_Observations.png?width=200&name=Collaborative_Analytics_Buyers_Guide_Market_Observations.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Collaborative_Analytics_Buyers_Guide_Market_Observations.png?width=100&name=Collaborative_Analytics_Buyers_Guide_Market_Observations.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Collaborative_Analytics_Buyers_Guide_Market_Observations.png?width=200&name=Collaborative_Analytics_Buyers_Guide_Market_Observations.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Collaborative_Analytics_Buyers_Guide_Market_Observations.png?width=300&name=Collaborative_Analytics_Buyers_Guide_Market_Observations.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Collaborative_Analytics_Buyers_Guide_Market_Observations.png?width=400&name=Collaborative_Analytics_Buyers_Guide_Market_Observations.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Collaborative_Analytics_Buyers_Guide_Market_Observations.png?width=500&name=Collaborative_Analytics_Buyers_Guide_Market_Observations.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Collaborative_Analytics_Buyers_Guide_Market_Observations.png?width=600&name=Collaborative_Analytics_Buyers_Guide_Market_Observations.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">The 2023 Ventana Research Buyers Guide for Collaborative Analytics research enables me to provide observations about how the market has advanced. </span></p> </div> <a href="https://davidmenninger.isg-research.net/collaborative-analytics-buyers-guide-market-observations"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics-data">Analytics & Data</a>, <a href="https://davidmenninger.isg-research.net/topic/collaborative-analytics">Collaborative Analytics</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/the-buyers-guide-for-embedded-analytics-classifies-and-rates-vendors">The Buyers Guide for Embedded Analytics Classifies and Rates Vendors</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">11 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png?width=100&name=The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png?width=300&name=The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png?width=400&name=The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png?width=500&name=The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png?width=600&name=The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The </span><a href="https://www.ventanaresearch.com/buyers_guide/analytics/embedded_analytics_2023"><span data-contrast="none">Ventana Research 2023 Embedded Analytics Buyers Guide</span></a><span data-contrast="auto"> is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics vendors supporting the spectrum...</span></p> </div> <a href="https://davidmenninger.isg-research.net/the-buyers-guide-for-embedded-analytics-classifies-and-rates-vendors"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/embedded-analytics">embedded analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</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/embedded-analytics-buyers-guide-market-observations">Embedded Analytics Buyers Guide: Market Observations</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">10 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Embedded_Analytics_Buyers_Guide_Market_Observations.png?width=200&name=Embedded_Analytics_Buyers_Guide_Market_Observations.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Embedded_Analytics_Buyers_Guide_Market_Observations.png?width=100&name=Embedded_Analytics_Buyers_Guide_Market_Observations.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Embedded_Analytics_Buyers_Guide_Market_Observations.png?width=200&name=Embedded_Analytics_Buyers_Guide_Market_Observations.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Embedded_Analytics_Buyers_Guide_Market_Observations.png?width=300&name=Embedded_Analytics_Buyers_Guide_Market_Observations.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Embedded_Analytics_Buyers_Guide_Market_Observations.png?width=400&name=Embedded_Analytics_Buyers_Guide_Market_Observations.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Embedded_Analytics_Buyers_Guide_Market_Observations.png?width=500&name=Embedded_Analytics_Buyers_Guide_Market_Observations.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Embedded_Analytics_Buyers_Guide_Market_Observations.png?width=600&name=Embedded_Analytics_Buyers_Guide_Market_Observations.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">The 2023 Ventana Research Buyers Guide for Embedded Analytics research enables me to provide observations about how the market has advanced. </span></p> </div> <a href="https://davidmenninger.isg-research.net/embedded-analytics-buyers-guide-market-observations"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/embedded-analytics">embedded analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</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/the-buyers-guide-for-augmented-analytics-classifies-and-rates-vendors">The Buyers Guide for Augmented Analytics Classifies and Rates Vendors</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">06 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png?width=100&name=The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png?width=300&name=The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png?width=400&name=The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png?width=500&name=The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png?width=600&name=The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The </span><a href="https://www.ventanaresearch.com/buyers_guide/analytics/augmented_analytics_2023"><span data-contrast="none">Ventana Research 2023 Augmented Analytics Buyers Guide</span></a><span data-contrast="auto"> is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics and Data vendors supporting...</span></p> </div> <a href="https://davidmenninger.isg-research.net/the-buyers-guide-for-augmented-analytics-classifies-and-rates-vendors"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</a>, <a href="https://davidmenninger.isg-research.net/topic/augmented-analytics">Augmented Analytics</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/augmented-analytics-buyers-guide-2023-market-observations">Augmented Analytics Buyers Guide 2023: Market Observations</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">05 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png?width=200&name=Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png?width=100&name=Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png?width=200&name=Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png?width=300&name=Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png?width=400&name=Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png?width=500&name=Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png?width=600&name=Augmented_Analytics_Buyers_Guide_2023_Market_Observations.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">The 2023 Ventana Research Buyers Guide for Augmented Analytics research enables me to provide observations about how the market has advanced. </span></p> </div> <a href="https://davidmenninger.isg-research.net/augmented-analytics-buyers-guide-2023-market-observations"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</a>, <a href="https://davidmenninger.isg-research.net/topic/augmented-analytics">Augmented Analytics</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/the-buyers-guide-for-analytics-and-data-classifies-and-rates-vendors">The Buyers Guide for Analytics and Data Classifies and Rates Vendors</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">04 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png?width=100&name=The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png?width=200&name=The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png?width=300&name=The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png?width=400&name=The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png?width=500&name=The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png?width=600&name=The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The </span><a href="https://www.ventanaresearch.com/buyers_guide/analytics/analytics_and_data_2023"><span data-contrast="none">Ventana Research 2023 Analytics and Data Buyers Guide</span></a><span data-contrast="auto"> is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics vendors supporting the spectrum...</span></p> </div> <a href="https://davidmenninger.isg-research.net/the-buyers-guide-for-analytics-and-data-classifies-and-rates-vendors"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics-data">Analytics & Data</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/analytics-and-data-buyers-guide-2023-market-observations">Analytics and Data Buyers Guide 2023: Market Observations</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">03 October 2023 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png?width=200&name=Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png?width=100&name=Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png?width=200&name=Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png?width=300&name=Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png?width=400&name=Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png?width=500&name=Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png?width=600&name=Analytics_and_Data_Buyers_Guide_2023_Market_Observations.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>The 2023 Ventana Research Buyers Guide for Analytics and Data research enables me to provide observations about how the market has advanced.</p> </div> <a href="https://davidmenninger.isg-research.net/analytics-and-data-buyers-guide-2023-market-observations"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics-data">Analytics & Data</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;" src="https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=100&name=ISG_Bug_Reverse_Transparent.png" alt="ISG Software Research" width="100" data-constrained="true" caption="false" srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=50&name=ISG_Bug_Reverse_Transparent.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=100&name=ISG_Bug_Reverse_Transparent.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=150&name=ISG_Bug_Reverse_Transparent.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=200&name=ISG_Bug_Reverse_Transparent.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=250&name=ISG_Bug_Reverse_Transparent.png 250w, 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class="filter-link-count" dir="ltr">(12)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/cloud">Cloud <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/cloud-computing">Cloud Computing <span class="filter-link-count" dir="ltr">(61)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/cloudera">Cloudera <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/collaboration">Collaboration <span class="filter-link-count" dir="ltr">(89)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/collaboration-for-business">collaboration for business <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/collaborative-conversational-computing">Collaborative & Conversational Computing <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/collaborative-analytics">Collaborative Analytics <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/collaborative-computing">collaborative computing <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/complex-event-processing">Complex Event Processing <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/computer-vision">Computer Vision <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/conversational-computing">Conversational Computing <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/customer-contact-center">Customer & Contact Center <span class="filter-link-count" dir="ltr">(37)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/customer-experience">Customer Experience <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/customer-service">Customer Service <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/dashboards">Dashboards <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data">Data <span class="filter-link-count" dir="ltr">(73)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-analytics">Data Analytics <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-catalog">Data catalog <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-governance">Data Governance <span class="filter-link-count" dir="ltr">(76)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-integration">Data Integration <span class="filter-link-count" dir="ltr">(29)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-intelligence">Data Intelligence <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-lake">Data Lake <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-lakes">data lakes <span class="filter-link-count" dir="ltr">(25)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-management">Data Management <span class="filter-link-count" dir="ltr">(24)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-operations">data operations <span class="filter-link-count" dir="ltr">(15)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-platforms">Data Platforms <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-preparation">Data Preparation <span class="filter-link-count" dir="ltr">(64)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-quality">Data Quality <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-science">Data Science <span class="filter-link-count" dir="ltr">(32)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-scientist">Data Scientist <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-storage">Data Storage <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-virtualization">Data Virtualization <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-visualization">Data Visualization <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/data-warehousing">Data Warehousing <span class="filter-link-count" dir="ltr">(12)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/database">Database <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/datameer">Datameer <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/dataops">dataops <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/datawatch">Datawatch <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/decision-intelligence">Decision Intelligence <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/deep-learning">Deep Learning <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/digital-business">Digital Business <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/digital-commerce">Digital Commerce <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/digital-technology">Digital Technology <span class="filter-link-count" dir="ltr">(82)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/domo">Domo 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href="https://davidmenninger.isg-research.net/topic/event-data">Event Data <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/event-stream-processing">Event Stream Processing <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/event-streams">Event Streams <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/exalytics">Exalytics <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/explorium">Explorium <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/extended-reality">extended reality <span class="filter-link-count" 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 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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 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"@context": "http://schema.org", "@type": "BlogPosting", "headline": "Stream and Event Processing Require Real-Time Analytics", "mainEntityOfPage": "https://davidmenninger.isg-research.net/stream-and-event-processing-require-real-time-analytics", "datePublished": "25/10/2023", "dateModified": "25/10/2023", "articleBody": "In my past perspectives, I’ve written about the evolution from data at rest to data in motion and the fact that you can’t rely on dashboards for real-time analytics. Organizations are becoming more and more event-driven and operating based on streaming data. As well, analytics are becoming more and more intertwined with operations. More than one-fifth of organizations (22%) describe their analytics workloads as real time in our Data and Analytics Benchmark Research and nearly half (47%) of organizations report their IoT workloads require seconds or sub-second latency. If organizations can’t rely on dashboards for real-time analytics, what should they consider? Let’s start with a consideration of the requirements for real-time analytics. Clearly, latency is one consideration. The analysis must be completed quickly enough to meet the requirements of the specific use case. Some use cases require very low latency, such as digital ad servers. Other use cases, such as social media monitoring, are less demanding. But in either case, one of the key requirements is automation. Manually monitoring continuous streams of data is not a very effective or efficient way to analyze and respond to events as they occur. Another question is how much context is needed to provide an accurate analysis. In some cases, a single event might be sufficient, for instance if you are monitoring temperature and need to know if any single reading is outside normal operating limits. In other cases, you may need a window of events, such as social media monitoring, to see if sentiment has shifted over a period of time. And in still other situations, you may need large amounts of historical context, for example a customer’s past purchase history, so you can make product recommendations as they are browsing your site or speaking with a customer service agent. The options to handle these requirements fall into two broad categories: data platforms and stream-processing frameworks. My colleague, Matt Aslett, has written about and evaluated operational data platforms. Data platform vendors, both relational and non-relational (NoSQL), have been reducing the latency and increasing the throughput of their systems. In many use cases, these capabilities may be sufficient. In other cases, organizations may need to consider a stream-processing framework, or they may have already adopted a streaming data platform and wish to enrich the data as it streams through their organization. There are a variety of Apache open-source projects associated with processing streaming data including Beam, Calcite, Flink, Kafka, Spark, Storm and others. Among these, Kafka and Spark have been widely adopted. Kafka has emerged as a de facto standard for streaming data, with many vendors supporting it in their data platforms or offering it as a managed service. However, while Kafka provides a robust data streaming platform, it is limited in the types of transformations and analyses it supports. Perhaps as a result of these limitations, Apache Flink is on a growth trajectory that matches Kafka’s earlier growth trajectory. Flink provides stateful computations over data streams, including an SQL processing layer. Apache Spark has also emerged as a de facto standard for processing large amounts of data and is the backbone of many data lake implementations. Within Spark are projects to support SQL as well as a project for Structured Streaming which applies SQL to streaming data. For those that require more sophisticated analyses, Spark also includes a machine learning (ML) library. Basically, organizations have three categories to choose from for real-time analytics over streaming data. First, they can rely on their data platform provider. Most are offering some support for stream processing and, depending on the use case and the relationship with the vendor, that may be sufficient. For those organizations that have made big commitments to a data lake architecture, Spark is likely to be a good alternative, again depending on the use case. However, for those organizations that are heavily invested in Kafka or one of its variants, Flink may be the best option, enabling the analyses to be associated with the streams independent of where they land and what data platforms are used. Some operations don’t require real time. Some require near real time and still others will require nearly instantaneous responses. Explore your options so you can be prepared to meet your organization’s needs. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/Stream_and_Event_Processing_Require_Real-Time_Analytics.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": "The Buyers Guide for Mobile Analytics Classifies and Rates Vendors", "mainEntityOfPage": "https://davidmenninger.isg-research.net/the-buyers-guide-for-mobile-analytics-classifies-and-rates-vendors", "datePublished": "17/10/2023", "dateModified": "17/10/2023", "articleBody": "I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 Mobile Analytics Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics vendors supporting the spectrum of Mobile Analytics. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the product experience ﹘ Adaptability, Capability, Manageability, Reliability and Usability ﹘ and two related to the customer experience ﹘ TCO/ROI and vendor Validation. This research-based index evaluates the full business and information technology value of Mobile Analytics software offerings. I encourage you to learn more about our Buyers Guide and its effectiveness as a vendor selection and RFI/RFP tool. This Buyers Guide research evaluates the following vendors that offer products for Mobile Analytics as we define it: AWS, Cloud Software Group, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau (Salesforce), ThoughtSpot and Zoho. 11 of these 22 suppliers responded positively to our requests for information and provided completed questionnaires and demonstrations to aid our analysis of their Mobile Analytics products. Along with briefings and information where provided, all online material that was generally available was used for the analysis. This report includes products generally available as of August 1, 2023. The following vendors declined to participate or did not respond to our invitation: AWS, Cloud Software Group, Google, Idera, Microsoft, SAS, Sigma Computing and ThoughtSpot. To organizations considering products from these vendors, we recommend extra scrutiny as part of the software assessment because they did not make their technology available for the Value Index evaluation process. Unlike many IT analyst firms that rank vendors from an IT-only perspective or focus on a specific type of Mobile Analytics, Ventana Research has designed the Buyers Guide to provide a balanced perspective, rooted in an understanding of business drivers and needs. This approach not only reduces cost and time but also minimizes the risk of making a decision that is bad for the business. Using the Buyers Guide will enable your organization to achieve levels of efficiency and effectiveness needed to optimize Mobile Analytics. We urge organizations to do a thorough job of evaluating Mobile Analytics offerings in this Buyers Guide as both the results of our in-depth analysis of these vendors and as an evaluation methodology. The Value Index can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP. The Buyers Guide for Mobile Analytics in 2023 finds Oracle first on the list, followed by SAP and Qlik. Companies that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader. The Leaders in Product Experience are: Oracle. SAP. IBM. The Leaders in Customer Experience are: Oracle. SAP. Qlik. The Leaders across any of the seven categories are: Oracle, which has achieved this rating in six of the seven categories. SAP in four categories. IBM in three categories. Domo and Qlik in two categories. Microsoft, MicroStrategy, Sisense and Tableau in one category. The overall performance chart provides a visual representation of how vendors rate across product and customer experience. Vendors with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, vendors that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as vendors of “merit.” Vendors that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating. Note that close vendor scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every organization or process. Although there is a high degree of commonality in how organizations handle mobile analytics there are many idiosyncrasies and differences that can make one vendor’s offering a better fit than another. After more than a decade of technological advances, all the products we evaluated are feature-rich, but not all the capabilities they offer are equally valuable to users. Moreover, the existence of too many capabilities may be a negative factor for an organization if it introduces unnecessary complexity. Nonetheless, an organization may decide that a larger number of options is a plus, especially if some of them match its established practices or better support a new initiative that is driving the purchase of new software. Features, functions and vendor assessments are not the only deciding factors. For example, an organization may face budget constraints such that the TCO evaluation can tip the scale to one vendor or another. This is where the Value Index methodology and appropriate weighting can be applied to determine the best fit of vendors and products to an organization’s specific needs. Our firm has made every effort to encompass in this Buyers Guide the overall product and customer experience from our Mobile Analytics blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which vendor and products best fit an organization’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects. You can find more details on our site as well as in the Buyers Guide Report. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/The_Buyers_Guide_for_Mobile_Analytics_Classifies_and_Rates_Vendors.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": "Mobile Analytics Buyers Guide: Market Observations", "mainEntityOfPage": "https://davidmenninger.isg-research.net/mobile-analytics-buyers-guide-market-observations", "datePublished": "16/10/2023", "dateModified": "16/10/2023", "articleBody": "The 2023 Ventana Research Buyers Guide for Mobile Analytics research enables me to provide observations about how the market has advanced. The processes and technology of the mobile analytics software industry play an instrumental role in enabling an organization’s business units and IT to optimally utilize data in both tactical and strategic ways. To accomplish this, organizations must provide technology that can access the data, generate and apply insights from analytics, communicate the results and support collaboration as needed. For analytics to be effective, they need to be available to line-of-business personnel as needed in their normal course of conducting business, which today means providing rich mobile access to analytics to support a mobile workforce seeking to conduct business in any location at any time. Workers today expect these mobile capabilities, so organizations must make choices to provide analytics platforms that can deliver. Many of these workers switch between desktop/laptop devices when in the office to mobile devices when outside the office or even when attending an internal meeting, so integration between these two modes is important as well. This Buyers Guide assessment focuses on the challenge of delivering analytics and business intelligence (BI) on a variety of mobile devices including smartphones and tablets. When it comes to smaller devices such as smartphones, it may not be realistic to expect full-blown analyses due to the small form factor, but screen resolution on larger devices such as tablets can support nearly any type of functionality that mobile personnel may need. These needs are substantial: two-thirds of organizations (67%) consider it important to access analytics from mobile devices and more than two-fifths (45%) of organizations report that it is important or very important to be able to address data preparation tasks on mobile devices. Analytics vendors are divided in their approach to providing mobile capabilities. Many vendors have invested in developing applications that are native to the two platforms that dominate the mobile landscape: Apple’s iOS and Google’s Android operating system. Other vendors have opted to invest in an HTML5 approach, often in combination with a helper application that provides some of the native capabilities such as participation in the store or marketplace where applications are distributed. Our research suggests that both approaches can be effective. Vendors also differ in their approach to designing the mobile applications. Some take a design once, deploy anywhere approach where every visualization is available on all devices. This approach requires some interpretation on what the best mobile layout might be for each analysis. For instance, a dashboard may consist of four individual visualizations each occupying one quadrant of the display. On a small mobile device such as a smartphone, these are often presented with each visualization occupying the entire screen and vertical scrolling enabled to move through all four. Other vendors offer a mobile design view that offers the opportunity not only to preview how the devices will display information but to design visualizations specifically for mobile devices. The former approach makes it easier to build and manage the applications. The latter allows for more control over the use of limited screen real estate for mobile devices. The small form factor of these mobile devices, especially smartphones, has helped push the boundaries on ease of use. Users can’t be expected to make multiple selections and accomplish complex interactions using a small display, so vendors have simplified how tasks are performed. In addition, mobile devices offer capabilities such as voice interaction, location information and cameras that can enhance the user experience. Voice interaction can be used for natural language query and natural language responses, and we are starting to see multilingual natural language capabilities. As support for wearables becomes more prevalent, voice interaction could make those devices much more interactive. In some cases, mobile device information can be used to initiate queries or charts based on a customer or vendor’s location information. Cameras can identify products on retail store shelves and their location to help drive sales analyses and projections. We also see a growing interest in — and a growing set of capabilities for — collaboration in conjunction with analytics. Two-thirds of organizations report they are using or plan to use collaboration with analytics. Collaboration provides a way for organizations to derive more value from their analytics by sharing results and interacting with others who can put the information to use in the operations of the business. Collaboration also helps make it easier for individuals to find the information or analyses they need more quickly. Mobile technology is critical for successful collaboration because it reaches so far into the community of potential collaborators. They can be informed via their mobile devices that a topic of interest requires their input or that new information is available. This research evaluates the following vendors that offer products that address key elements of mobile data as we define it: AWS, Cloud Software Group, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau (Salesforce), ThoughtSpot and Zoho. You can find more details on our site as well as in the Buyers Guide Market Report. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/Mobile_Analytics_Buyers_Guide_Market_Observations.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": "The Buyers Guide for Collaborative Analytics Classifies and Rates Vendors", "mainEntityOfPage": "https://davidmenninger.isg-research.net/the-buyers-guide-for-collaborative-analytics-classifies-and-rates-vendors", "datePublished": "13/10/2023", "dateModified": "13/10/2023", "articleBody": "I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 Collaborative Analytics Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics vendors supporting the spectrum of Collaborative Analytics. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the product experience ﹘ Adaptability, Capability, Manageability, Reliability and Usability ﹘ and two related to the customer experience ﹘ TCO/ROI and vendor Validation. This research-based index evaluates the full business and information technology value of collaborative analytics software offerings. I encourage you to learn more about our Buyers Guide and its effectiveness as a vendor selection and RFI/RFP tool. This Buyers Guide research evaluates the following vendors that offer products for Collaborative Analytics as we define it: AWS, Cloud Software Systems, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau, ThoughtSpot and Zoho. 11 of these 22 suppliers responded positively to our requests for information and provided completed questionnaires and demonstrations to aid our analysis of their Collaborative Analytics products. Along with briefings and information where provided, all online material that was generally available was used for the analysis. This report includes products generally available as of August 1, 2023. The following vendors declined to participate or did not respond to our invitation: AWS, Cloud Software Group, Google, Idera, Microsoft, SAS, Sigma Computing and ThoughtSpot. To organizations considering products from these vendors, we recommend extra scrutiny as part of the software assessment because they did not make their technology available for the Value Index evaluation process. Unlike many IT analyst firms that rank vendors from an IT-only perspective or focus on a specific type of Collaborative Analytics, Ventana Research has designed the Buyers Guide to provide a balanced perspective, rooted in an understanding of business drivers and needs. This approach not only reduces cost and time but also minimizes the risk of making a decision that is bad for the business. Using the Buyers Guide will enable your organization to achieve levels of efficiency and effectiveness needed to optimize Collaborative Analytics. We urge organizations to do a thorough job of evaluating Collaborative Analytics offerings in this Buyers Guide as both the results of our in-depth analysis of these vendors and as an evaluation methodology. The Value Index can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP. The Buyers Guide for Collaborative Analytics in 2023 finds SAP first on the list, followed by IBM and Domo. Companies that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader. The Leaders in Product Experience are: SAP. IBM. Domo. The Leaders in Customer Experience are: Oracle. SAP. Qlik. The Leaders across any of the seven categories are: Oracle, which has achieved this rating in six of the seven categories. SAP in five categories. IBM in four categories. Domo and Qlik in two categories. Sisense and Tableau in one category. The overall performance chart provides a visual representation of how vendors rate across product and customer experience. Vendors with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, vendors that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as vendors of “merit.” Vendors that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating. Note that close vendor scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every organization or process. Although there is a high degree of commonality in how organizations handle Collaborative Analytics, there are many idiosyncrasies and differences that can make one vendor’s offering a better fit than another. After more than a decade of technological advances, all the products we evaluated are feature-rich, but not all the capabilities they offer are equally valuable to users. Moreover, the existence of too many capabilities may be a negative factor for an organization if it introduces unnecessary complexity. Nonetheless, an organization may decide that a larger number of options is a plus, especially if some of them match its established practices or better support a new initiative that is driving the purchase of new software. Features, functions and vendor assessments are not the only deciding factors. For example, an organization may face budget constraints such that the TCO evaluation can tip the scale to one vendor or another. This is where the Value Index methodology and appropriate weighting can be applied to determine the best fit of vendors and products to an organization’s specific needs. Our firm has made every effort to encompass in this Buyers Guide the overall product and customer experience from our Collaborative Analytics blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which vendor and products best fit an organization’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects. You can find more details on our site as well as in the Buyers Guide Report. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/The_Buyers_Guide_for_Collaborative_Analytics_Classifies_and_Rates_Vendors.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": "Collaborative Analytics Buyers Guide: Market Observations", "mainEntityOfPage": "https://davidmenninger.isg-research.net/collaborative-analytics-buyers-guide-market-observations", "datePublished": "12/10/2023", "dateModified": "12/10/2023", "articleBody": "The 2023 Ventana Research Buyers Guide for Collaborative Analytics research enables me to provide observations about how the market has advanced. Analytics almost universally involves collaboration among a team of individuals. Interpreting the results of the analyses, choosing a course of action and tracking the implementation of those actions spans multiple roles and departments within an organization. As a result, most of today’s analytics and business intelligence (BI) products support some form of collaboration. Capabilities that support the sharing of — and communication about — output from analytical processes help organizations maximize the value of their analytics investments. Facilitating communication and collaboration among those involved in the decision-making process leads to more informed and better decisions. Our research shows that nearly four in 10 organizations are using collaboration to support analytics processes, and more than one-half said they expect to use these capabilities in the future. Analytics and BI vendors have recognized the value of collaboration and have increasingly been incorporating these capabilities into their products. More than a decade ago, social media tools like Facebook, Twitter and LinkedIn brought on a wave of collaborative analytics and BI capabilities. We saw chat streams associated with specific analyses that users could like or endorse. The number of contributions a user made to the community was part of his or her profile so others could accordingly weigh the importance of the input. However, after an initial surge of interest, these efforts failed to gain traction and waned. Collaboration requires a large community of active individuals, and there simply were not enough people regularly engaged in using the analytic products. Those early efforts also required users to participate in the dialog from within the analytics and BI products. Rather than working solely with those products, line-of-business personnel spend their days using a variety of business applications. Two major changes now provide the glue to pull a community of collaborators together: mobile devices and enterprise collaboration tools. The significant expansion of mobile analytics and BI has made it easier for users to get involved. Perhaps more importantly, in the same way the social media users get notifications of activity via mobile devices, collaborative analytics and BI vendors use mobile notifications to engage participants in the analytics process. Organizations have also adopted more widespread use of enterprise collaboration technologies in place of or in addition to email and is more widely available. The analytics process typically involves multiple people with differing areas of expertise and responsibilities. Collaborative tools can enable this diverse group of participants to coordinate their activities and share knowledge. To be most effective, collaborative capabilities should cover the entire data and analytics process; only this way can participants understand the provenance of data as it is analyzed. With this approach, it is easy to identify subject matter experts to engage in the dialog. The team can discuss and document decision-making for compliance purposes, and the actions resulting from those decisions can be assigned and tracked to completion. We expect that by 2025, 8 in 10 BI software platforms will include collaborative capabilities designed to support organizations’ decision-making, task management and compliance requirements associated with analytics. These types of capabilities should be a standard part of analytic processes in much the same way that visualization is now a standard part of data and analytic processes. As organizations embrace more sophisticated analytics such as artificial intelligence (AI) and machine learning (ML), and as analytics become more easily accessible via technologies such as natural language processing (NLP), collaboration capabilities will become even more important. However, strong collaboration capabilities alone are insufficient. These capabilities also must include strong analytics. Our Value Index assessment methodology takes all these factors into account. This research evaluates the following vendors that offer products that address key elements of collaborative analytics as we define it: AWS, Cloud Software Systems, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau, ThoughtSpot and Zoho. You can find more details on our site as well as in the Buyers Guide Market Report. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/Collaborative_Analytics_Buyers_Guide_Market_Observations.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": "The Buyers Guide for Embedded Analytics Classifies and Rates Vendors", "mainEntityOfPage": "https://davidmenninger.isg-research.net/the-buyers-guide-for-embedded-analytics-classifies-and-rates-vendors", "datePublished": "11/10/2023", "dateModified": "11/10/2023", "articleBody": "I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 Embedded Analytics Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics vendors supporting the spectrum of Embedded Analytics. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the product experience ﹘ Adaptability, Capability, Manageability, Reliability and Usability ﹘ and two related to the customer experience ﹘ TCO/ROI and vendor Validation. This research-based index evaluates the full business and information technology value of Embedded Analytics software offerings. I encourage you to learn more about our Buyers Guide and its effectiveness as a vendor selection and RFI/RFP tool. This Buyers Guide research evaluates the following vendors that offer products for Embedded Analytics as we define it: AWS, Cloud Software Group, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau Software, ThoughtSpot and Zoho. 11 of these 22 suppliers responded positively to our requests for information and provided completed questionnaires and demonstrations to aid our analysis of their embedded analytics products. Along with briefings and information where provided, all online material that was generally available was used for the analysis. This report includes products generally available as of August 1, 2023. The following vendors declined to participate or did not respond to our invitation: AWS, Cloud Software Group, Google, Idera, Microsoft, SAS, Sigma Computing and ThoughtSpot. To organizations considering products from these vendors, we recommend extra scrutiny as part of the software assessment because they did not make their technology available for the Value Index evaluation process. Unlike many IT analyst firms that rank vendors from an IT-only perspective or focus on a specific type of Embedded Analytics, Ventana Research has designed the Buyers Guide to provide a balanced perspective, rooted in an understanding of business drivers and needs. This approach not only reduces cost and time but also minimizes the risk of making a decision that is bad for the business. Using the Buyers Guide will enable your organization to achieve levels of efficiency and effectiveness needed to optimize Embedded Analytics. We urge organizations to do a thorough job of evaluating Embedded Analytics offerings in this Buyers Guide as both the results of our in-depth analysis of these vendors and as an evaluation methodology. The Value Index can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP. The Buyers Guide for Embedded Analytics in 2023 finds IBM first on the list, followed by SAP and Qlik. Companies that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader. The Leaders in Product Experience are: IBM. SAP. Qlik. The Leaders in Customer Experience are: Oracle. SAP. Qlik. The Leaders across any of the seven categories are: IBM, Oracle and SAP, which has achieved this rating in five of the seven categories. Qlik, in three categories. Domo, in two categories. Sisense, in one category. The overall performance chart provides a visual representation of how vendors rate across product and customer experience. Vendors with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, vendors that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as vendors of “merit.” Vendors that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating. Note that close vendor scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every organization or process. Although there is a high degree of commonality in how organizations handle Embedded Analytics, there are many idiosyncrasies and differences that can make one vendor’s offering a better fit than another. After more than a decade of technological advances, all the products we evaluated are feature-rich, but not all the capabilities they offer are equally valuable to users. Moreover, the existence of too many capabilities may be a negative factor for an organization if it introduces unnecessary complexity. Nonetheless, an organization may decide that a larger number of options is a plus, especially if some of them match its established practices or better support a new initiative that is driving the purchase of new software. Features, functions and vendor assessments are not the only deciding factors. For example, an organization may face budget constraints such that the TCO evaluation can tip the scale to one vendor or another. This is where the Value Index methodology and appropriate weighting can be applied to determine the best fit of vendors and products to an organization’s specific needs. Our firm has made every effort to encompass in this Buyers Guide the overall product and customer experience from our Embedded Analytics blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which vendor and products best fit an organization’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects. You can find more details on our site as well as in the Buyers Guide Report. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/The_Buyers_Guide_for_Embedded_Analytics_Classifies_and_Rates_Vendors.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": "Embedded Analytics Buyers Guide: Market Observations", "mainEntityOfPage": "https://davidmenninger.isg-research.net/embedded-analytics-buyers-guide-market-observations", "datePublished": "10/10/2023", "dateModified": "10/10/2023", "articleBody": "The 2023 Ventana Research Buyers Guide for Embedded Analytics research enables me to provide observations about how the market has advanced. The processes and technology of the analytics and data software industry play an instrumental role in enabling an organization’s business units and IT to optimally utilize data in both tactical and strategic ways. To accomplish this, organizations must provide their workers technology that can access the data, generate and apply insights from analytics, communicate the results and support collaboration as needed. When analytics are embedded in business processes and applications, analyses are easier to perform and more accessible to line-of-business personnel. The analyses are easier to perform in part because the application collects and assembles data. Our research shows that data preparation can be the most time-consuming step in the analytical process; embedded analytics can dramatically reduce or eliminate this step. Analysis is also easier to consume because there is no need to switch context between the business application and an analysis tool. Perhaps more importantly, analytics embedded within applications can more easily lead to action. For instance, if an analysis suggests a change in pricing, the appropriate logic can be included in the application to make those changes. If an analysis suggests a marketing campaign for a specific customer segment, that segmentation can be performed and the campaign launched. For these reasons, we expect that by 2026, more than two-thirds of line-of-business personnel will have immediate access to cross-functional analytics embedded in their activities and processes, helping to make operational decision-making more efficient and effective. This Buyers Guide focuses on the challenge of delivering analytics and business intelligence in the context of business processes and applications. These needs are substantial — more than half of organizations (53%) report their users of analytics tools cannot perform their own analyses without IT involvement. Our research on cloud-based analytics, predictive analytics, data preparation and big data analytics all show strong interest in embedded delivery of those capabilities. Analytics vendors understand the need to deliver embedded analytics; most have been developing and enhancing APIs and other mechanisms to integrate analytics more tightly into business processes and applications. However, it can be challenging for analytics and business intelligence vendors to package and deliver their capabilities in a way that makes them easy to embed into other applications and processes. Vendors are working to overcome these challenges because organizations recognize the importance of embedded analytics. Nearly three-quarters of participants in our Analytics and Data Benchmark Research said they considered embedded analytics important. Vendors must provide tools for defining data models and accessing data from applications and other data sources. These tools will likely be used by a different audience than typical analytics tools. An application development team, for instance, would create the framework for line-of-business personnel to perform analyses. In addition, the tools must provide mechanisms to integrate both inputs to and outputs from the analytical processes with other applications. Embedded analytics also requires programmatic access to the management and administration functions to minimize installation and maintenance of the system for line-of-business personnel. Organizations are aware of the value of embedded analytics. The next step is to embrace embedded analytics and determine what capabilities their vendor currently offers. They should also be comparing their current offering with what other vendors have to offer. In evaluating embedded analytics, one must also consider the underlying analytics capabilities. Great APIs and SDKs can only do so much if the foundation of underlying analytics is weak. Consequently, this Buyers Guide combines an assessment of embedded analytics capabilities with core analytics capabilities to determine the vendor’s overall rankings. Organizations can then use this report not only to help guide purchasing decisions, but to guide conversations with vendors about their roadmap for embedded analytics. The market continues to evolve, but organizations can realize value today that will improve their analytics processes. This research evaluates the following vendors that offer products that address key elements of embedded analytics as we define it: AWS, Cloud Software Group, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau Software, ThoughtSpot and Zoho. You can find more details on our site as well as in the Buyers Guide Market Report. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/Embedded_Analytics_Buyers_Guide_Market_Observations.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": "The Buyers Guide for Augmented Analytics Classifies and Rates Vendors", "mainEntityOfPage": "https://davidmenninger.isg-research.net/the-buyers-guide-for-augmented-analytics-classifies-and-rates-vendors", "datePublished": "06/10/2023", "dateModified": "06/10/2023", "articleBody": "I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 Augmented Analytics Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics and Data vendors supporting the spectrum of Augmented Analytics. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the product experience ﹘ Adaptability, Capability, Manageability, Reliability and Usability ﹘ and two related to the customer experience ﹘ TCO/ROI and vendor Validation. This research-based index evaluates the full business and information technology value of Augmented Analytics software offerings. I encourage you to learn more about our Buyers Guide and its effectiveness as a vendor selection and RFI/RFP tool. This Buyers Guide research evaluates the following vendors that offer products for Augmented Analytics as we define it: AWS, Cloud Software Group, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau Software, ThoughtSpot and Zoho. 11 of these 22 suppliers responded positively to our requests for information and provided completed questionnaires and demonstrations to aid our analysis of their augmented analytics products. Along with briefings and information where provided, all online material that was generally available was used for the analysis. This report includes products generally available as of August 1, 2023. The following vendors declined to participate or did not respond to our invitation: AWS, Cloud Software Group, Google, Idera, Microsoft, SAS, Sigma Computing and ThoughtSpot. To organizations considering products from these vendors, we recommend extra scrutiny as part of the software assessment because they did not make their technology available for the Value Index evaluation process. Unlike many IT analyst firms that rank vendors from an IT-only perspective or focus on a specific type of Augmented Analytics, Ventana Research has designed the Buyers Guide to provide a balanced perspective, rooted in an understanding of business drivers and needs. This approach not only reduces cost and time but also minimizes the risk of making a decision that is bad for the business. Using the Buyers Guide will enable your organization to achieve levels of efficiency and effectiveness needed to optimize Augmented Analytics. We urge organizations to do a thorough job of evaluating Augmented Analytics offerings in this Buyers Guide as both the results of our in-depth analysis of these vendors and as an evaluation methodology. The Value Index can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP. The Buyers Guide for Augmented Analytics in 2023 finds Oracle first on the list, followed by SAP and IBM. Companies that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader. The Leaders in Product Experience are: Oracle. SAP. IBM. The Leaders in Customer Experience are: Oracle. SAP. Qlik. The Leaders across any of the seven categories are: Oracle, which has achieved this rating in six of the seven categories. SAP, in five categories. IBM, in four categories. Domo and Qlik, in two categories. Sisense and Tableau, in one category. The overall performance chart provides a visual representation of how vendors rate across product and customer experience. Vendors with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, vendors that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as vendors of “merit.” Vendors that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating. Note that close vendor scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every organization or process. Although there is a high degree of commonality in how organizations handle Augmented Analytics, there are many idiosyncrasies and differences that can make one vendor’s offering a better fit than another. After more than a decade of technological advances, all the products we evaluated are feature-rich, but not all the capabilities they offer are equally valuable to users. Moreover, the existence of too many capabilities may be a negative factor for an organization if it introduces unnecessary complexity. Nonetheless, an organization may decide that a larger number of options is a plus, especially if some of them match its established practices or better support a new initiative that is driving the purchase of new software. Features, functions and vendor assessments are not the only deciding factors. For example, an organization may face budget constraints such that the TCO evaluation can tip the scale to one vendor or another. This is where the Value Index methodology and appropriate weighting can be applied to determine the best fit of vendors and products to an organization’s specific needs. Our firm has made every effort to encompass in this Buyers Guide the overall product and customer experience from our Augmented Analytics blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which vendor and products best fit an organization’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/The_Buyers_Guide_for_Augmented_Analytics_Classifies_and_Rates_Vendors.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": "Augmented Analytics Buyers Guide 2023: Market Observations", "mainEntityOfPage": "https://davidmenninger.isg-research.net/augmented-analytics-buyers-guide-2023-market-observations", "datePublished": "05/10/2023", "dateModified": "05/10/2023", "articleBody": "The 2023 Ventana Research Buyers Guide for Augmented Analytics research enables me to provide observations about how the market has advanced. For decades, organizations have been improving and expanding the way they use analytics and data software, commonly referred to as business intelligence (BI), to improve their operations. Vendors have made dramatic improvements to BI products with highly interactive visualizations and the ability to process and display very large volumes of data quickly. However, organizations quest for more. Artificial intelligence and machine learning (AI/ML) has gained in popularity with 87% of participants in our Analytics and Data Benchmark Research indicating they have adopted or plan to adopt AI/ML. Adopting AI/ML has proven more complicated than many had expected. Ideally, BI software products could simply be extended to include a full set of AI/ML capabilities, but that has not yet happened. AI/ML requires skills that are beyond the reach of many analysts, and organizations have had difficulty finding skilled resources. As a result, we expect through 2025, AI and ML approaches will remain largely independent of BI approaches, requiring three-quarters of organizations to maintain multiple, separate skill sets. Faced with this separation, BI software vendors have invested in ways to make AI/ML more accessible by augmenting the capabilities in their products. These combined capabilities have been referred to as augmented analytics or augmented intelligence. This report uses the term augmented analytics. AI/ML can augment analytics in a variety of ways. Natural language processing (NLP) utilizes AI/ML to parse and understand language to support conversational analytics with natural language queries and narrative responses. Automated machine learning (AutoML) automates the process of creating ML models, making more sophisticated analytics such as customer segmentation using clustering techniques accessible to more individuals. And, AI/ML can be applied to many tasks in analytics and data processes to make those tasks easier to perform. Perhaps the most common area to apply AI/ML assistance is in data preparation. Data preparation continues to be the area where organizations spend the most time in their analytics processes. AI/ML can be used to suggest which tables of data to combine and how to combine those tables. It can be used to automatically construct a logical data model from a physical data model. AI/ML can augment data quality processes, identifying outliers and anomalies in the data, even recommending potential corrections for those data points. While efforts to apply AI/ML have been underway for some time, the sudden explosion of generative AI capabilities has fueled more interest in how to augment BI. Generative AI is being used to generate SQL to access data sources, and to enhance NLP and conversational analytics. In some cases, generative AI is being used to produce documentation of data pipelines used in analytics processes, enhancing the understanding and lineage of the data. In some ways, it is the wild, wild west, with vendors racing to outdo each other in the ways in which they can apply generative AI. The technology holds much promise, and we expect it will have a significant impact on the analytics market, but it is early days still. Augmented analytics will continue to evolve. Generative AI is likely to make conversational analytics more common and more capable than it is today. It may enable better support for multilingual capabilities currently lacking in most analytics products and will likely lead to increased automation in data preparation processes and in creating initial analyses, making analysts much more productive. More products will offer AutoML capabilities. Among the vendors we evaluated, AutoML is most often used to generate forecasts and to perform customer segmentation analyses. Over time, AutoML capabilities will expand to support more types of analyses and will produce models with improved accuracy. The exact intersection between AutoML in augmented analytics products and the models produced from more sophisticated AI/ML products remains to be seen. Today some of the augmented analytics products can work with these models, but it still a loosely coupled process. Organizations should be aware of the changes going on in the market, and should understand what capabilities their vendor currently offers. They should also be comparing their current offering with what other vendors have to offer. In evaluating augmented analytics, one must consider the underlying analytics capabilities. Great augmentation can only do so much if the foundation of underlying analytics is weak. Consequently, this Buyers Guide combines an assessment of augmented analytics capabilities with core analytics capabilities to determine the vendor’s overall rankings. Organizations can then use this report not only to help guide purchasing decisions, but to guide conversations with vendors about their roadmap for augmented analytics. The market is still evolving rapidly, but organizations can realize value today that will improve their analytics processes. This research evaluates the following analytics and data vendors that offer products that include key elements of augmented analytics as we define it: AWS, Cloud Software Group, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau Software, ThoughtSpot and Zoho. You can find more details on our site as well as in the Buyers Guide Market Report. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/Augmented_Analytics_Buyers_Guide_2023_Market_Observations.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": "The Buyers Guide for Analytics and Data Classifies and Rates Vendors", "mainEntityOfPage": "https://davidmenninger.isg-research.net/the-buyers-guide-for-analytics-and-data-classifies-and-rates-vendors", "datePublished": "04/10/2023", "dateModified": "04/10/2023", "articleBody": "I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 Analytics and Data Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics vendors supporting the spectrum of Analytics and Data. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the product experience ﹘ Adaptability, Capability, Manageability, Reliability and Usability ﹘ and two related to the customer experience ﹘ TCO/ROI and vendor Validation. This research-based index evaluates the full business and information technology value of analytics and data software offerings. I encourage you to learn more about our Buyers Guide and its effectiveness as a vendor selection and RFI/RFP tool. This Buyers Guide research evaluates the following vendors that offer products for Analytics and Data as we define it: AWS, Cloud Software Group, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau (Salesforce), ThoughtSpot and Zoho. 11 of these 22 suppliers responded positively to our requests for information and provided completed questionnaires and demonstrations to aid our analysis of their analytics and data products. Along with briefings and information where provided, all online material that was generally available was used for the analysis. This report includes products generally available as of August 1, 2023. The following vendors declined to participate or did not respond to our invitation: AWS, Cloud Software Group, Google, Idera, Microsoft, SAS, Sigma Computing and ThoughtSpot. To organizations considering products from these vendors, we recommend extra scrutiny as part of the software assessment because they did not make their technology available for the Value Index evaluation process. Unlike many IT analyst firms that rank vendors from an IT-only perspective or focus on a specific type of Analytics and Data, Ventana Research has designed the Buyers Guide to provide a balanced perspective, rooted in an understanding of business drivers and needs. This approach not only reduces cost and time but also minimizes the risk of making a decision that is bad for the business. Using the Buyers Guide will enable your organization to achieve levels of efficiency and effectiveness needed to optimize Analytics and Data. We urge organizations to do a thorough job of evaluating Analytics and Data offerings in this Buyers Guide as both the results of our in-depth analysis of these vendors and as an evaluation methodology. The Value Index can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP. The Buyers Guide for Analytics and Data in 2023 finds SAP first on the list, followed by IBM and Oracle. Companies that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader. The Leaders in Product Experience are: IBM. SAP. Oracle. The Leaders in Customer Experience are: Oracle. SAP. Qlik. The Leaders across any of the seven categories are: Oracle and SAP, which has achieved this rating in five of the seven categories. IBM, in four categories. Qlik and Domo, in two categories. Sisense and Tableau, in one category. The overall performance chart provides a visual representation of how vendors rate across product and customer experience. Vendors with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, vendors that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as vendors of “merit.” Vendors that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating. Note that close vendor scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every organization or process. Although there is a high degree of commonality in how organizations handle Analytics and Data, there are many idiosyncrasies and differences that can make one vendor’s offering a better fit than another. After more than a decade of technological advances, all the products we evaluated are feature-rich, but not all the capabilities they offer are equally valuable to users. Moreover, the existence of too many capabilities may be a negative factor for an organization if it introduces unnecessary complexity. Nonetheless, an organization may decide that a larger number of options is a plus, especially if some of them match its established practices or better support a new initiative that is driving the purchase of new software. Features, functions and vendor assessments are not the only deciding factors. For example, an organization may face budget constraints such that the TCO evaluation can tip the scale to one vendor or another. This is where the Value Index methodology and appropriate weighting can be applied to determine the best fit of vendors and products to an organization’s specific needs. Our firm has made every effort to encompass in this Buyers Guide the overall product and customer experience from our Analytics and Data blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which vendor and products best fit an organization’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/The_Buyers_Guide_for_Analytics_and_Data_Classifies_and_Rates_Vendors.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": "Analytics and Data Buyers Guide 2023: Market Observations", "mainEntityOfPage": "https://davidmenninger.isg-research.net/analytics-and-data-buyers-guide-2023-market-observations", "datePublished": "03/10/2023", "dateModified": "03/10/2023", "articleBody": "The 2023 Ventana Research Buyers Guide for Analytics and Data research enables me to provide observations about how the market has advanced. The processes and technology of the analytics and data software industry continue to play an instrumental role in enabling an organization’s business units and IT to optimally utilize data in both tactical and strategic ways. To accomplish this, organizations must provide technology that can access the data, generate and apply insights from analytics, communicate the results and support collaboration as needed. Analytics utilizes mathematics to create measurements and metrics that enable data to be evaluated in whatever form, in whatever tool or application is needed to provide insights and guide decision-making. In today’s data-driven world, organizations must use analytics to understand and plan the details of their operations across every department and across the lines of business and IT. Organizations use analytics to track costs, create staffing plans, assess employee and supplier performance, identify variances and plan corrective actions. Analytics also helps inform employees and facilitates communication throughout the organization to coordinate actions toward a common mission and specific objectives. Operating without analytics would be like flying a plane without an instrument panel. While analytics as a modern business tool dates back more than three decades, the elements of business intelligence (BI) today have expanded well beyond query, reporting, analysis and publishing. The tools now include the sourcing and integration of data and the use of analytics for planning and forecasting, as well as dashboards that present analytics in a variety of visualizations. Analytics today also enables presentations in the form of natural-language narratives with some vendors able to support multiple languages. The collaborative sharing of insights is helping to reduce the time to take action and make decisions. Artificial intelligence and machine learning (AI/ML) extend analytics, enabling it to classify, predict and suggest behaviors that will help improve business operations. Vendors have also begun using ML to analyze product usage data to enhance and streamline interactions, anticipating the best next step in the analytical process and then performing or recommending that step. Advanced analytics, which incorporate AI and ML, has become a staple in analytic processes. Organizations that analyze their data using machine-learning technology state that they gain a competitive advantage, improve customer experiences, increase sales and respond faster to opportunities. In light of these benefits, it is no surprise that nearly two-thirds of organizations report using machine learning today, and three-quarters of organizations in our research said they plan to increase their use of machine learning. The ultimate goal of analytics is to help organizations make and implement decisions that improve their operations and bottom line. The range of analytics capabilities has become known as decision intelligence. Decision intelligence involves analyzing historical performance, determining potential courses of action, evaluating the results of those actions and then identifying the best path forward. Ideally, these processes can be conducted on a self-service basis. Self-service analytics continues to be a goal for most organizations, and those that can achieve it report greater satisfaction with their use of analytics. Organizations that can access analytics without the assistance of IT are more satisfied than those who require the assistance of IT. Organizations seeking to provide self-service analytics also need to provide self-service data preparation. This is one of the areas where we have seen significant additional capabilities from multiple vendors in this evaluation. In many of our research studies, preparing data is reported as the most time-consuming part of the analytics process, and our research finds that a majority of organizations are not comfortable allowing business users to work with data that has not been integrated or prepared for them by IT. We expect self-service data preparation capabilities will reduce the often-necessary involvement of IT. While AI and ML still require highly specialized skills, vendors have used elements of AI and ML to provide augmented intelligence capabilities such as automated insights and key driver analyses that require little or no input from the line-of-business personnel using the tools. These augmented intelligence capabilities make it easier for a larger portion of the workforce to gain insights they might not see otherwise. Augmented intelligence also ensures more consistency in an organization’s analytics discipline because many of the analyses are automated ensuring the same types of information are available to all. For analytics to be effective, they must be accessible. Many vendors now use natural language processing (NLP) to make it easier to access and find information via search and to understand information through narratives explaining the analyses. Analytics also need to be available to line-of-business personnel as needed in their normal course of conducting business, which means providing rich mobile access to analytics to support a workforce seeking to conduct business in any location at any time. Workers today expect these mobile capabilities, so organizations must make choices to provide analytics and data platforms that can deliver. Collaboration in conjunction with analytics has finally become much more commonplace. Two-thirds of organizations report they are using or plan to use collaboration with analytics. Vendors now provide many ways to enable collaboration ranging from commenting on analyses to rating data sources. Others provide ways for organizations to assign tasks and track them to completion, helping to ensure that the value of analytics results in specific actions taken by the organization. Analytics should also lead to action. Organizations use a variety of operational applications where the decisions resulting from analyses are implemented. Embedding analytics directly into these systems makes it easier for line-of-business workers to access the information they need without having to use a different system, reducing the need for additional training. As vendors continue to build out rich APIs that provide access to nearly all the functionality of their products, some vendors are also providing prebuilt connections delivering analytical outputs into operational systems. Ventana Research asserts that by 2026, more than two-thirds of line-of-business personnel will have immediate access to cross-functional analytics embedded in their activities and processes, helping to make operational decision-making more efficient and effective. Analytics must also be timely. Organizations often operate 24/7. Information streams into business operations from a rapidly growing number of devices and sources. Without the ability to analyze this information as it occurs, organizations risk missing the opportunity to respond in the moment. Our research shows that one-half of organizations consider it essential to process streaming data and event information in seconds or milliseconds. As organizations seek expand the spectrum of their analytic requirements, a transition to enterprise-class analytics is an essential step forward. Vendors have responded to these broadening needs with additional capabilities. In some cases, those vendors have invested in developing additional capabilities themselves. In others, they have acquired software vendors that offer complementary capabilities to their existing portfolio. Not only have the capabilities expanded, but the number of vendors has proliferated as well. Despite this expansion, there are still few vendors that attempt to provide the entire spectrum of capabilities we evaluate in this assessment. You will likely need more than one vendor to meet all your analytic needs. This research evaluates the following vendors that offer products that address key elements of analytics and data as we define it: AWS, Cloud Software Group, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau (Salesforce), ThoughtSpot and Zoho. You can find more details on our site as well as in the Buyers Guide Market Report. 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David Menninger's Analyst Perspectives