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David Menninger's Analyst Perspectives | Streaming Analytics

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font-size:1.4em } .tf-footer-04 ul.social li{ display:inline-block } .tf-footer-04 ul.social li i{ border-radius:50%; padding:6px; margin:3px;opacity:1;color:#fff; width:42px; height:42px;display:flex; justify-content:center; align-items:center; -webkit-transition:all ease-in-out .3s; -o-transition:all ease-in-out .3s; transition:all ease-in-out .3s; font-size:18px } .tf-footer-04 ul.social li a:hover i{ opacity:.75 } .tf-footer-04 ul.social li:hover, ul.social li a:hover { opacity: 1; } .tf-footer-04 .footer-logo { margin-bottom: .8rem; padding-bottom: 3rem; } .tf-footer-04 ul.hs-menu-children-wrapper { list-style-type: none; padding: 0; } .tf-footer-04 li.hs-menu-item.hs-menu-depth-2 a { padding: 8px 20px; display: block; } .tf-footer-04 li.hs-menu-item.hs-menu-depth-2 a:hover { background: #000; color: #fff; } .tf-footer-04 .row.footer-row { -webkit-box-align: center; -ms-flex-align: center; align-items: center; } .tf-footer-04 .footer-logo-socials img { max-width: 100%; height: auto; } .tf-footer-04 .tf-footer-nav .hs-menu-wrapper>ul li:hover a, .tf-footer-04 .tf-footer-nav .hs-menu-wrapper > ul li a:hover { color: rgba(129, 206, 228,1.0); } @media only screen and (max-width: 768px) { .tf-footer-04 ul.social li { margin-right: 0.5rem; margin-left: 0; } .row.footer-row { -webkit-box-orient: vertical; -webkit-box-direction: reverse; -ms-flex-direction: column-reverse; flex-direction: column-reverse; } .tf-footer-04 .social { padding-bottom: 0.2rem; padding-top: 0; display: flex; justify-content: center; } .footer-row p { margin-bottom: 20px !important; text-align: center; } .tf-footer-04 .tf-footer-nav .hs-menu-wrapper > ul li, .tf-footer-04 .tf-footer-nav .hs-menu-wrapper > ul li a { line-height: 3; } } .footer-heading { padding-bottom: 5px; margin-top: 20px; } .footer-logo-socials { margin: 40px 0 0 } .tf-footer-04 .tf-footer-nav .hs-menu-wrapper>ul { display: block } .footer-row p { margin-bottom: 0 } .footer-email { padding-bottom: 60px; max-width: 550px; margin: auto; position: relative } .footer-email .actions .hs-button { transition: all .15s ease-in-out; animation-timing-function: ease-in-out; font-family: Poppins, sans-serif; font-style: normal; font-weight: 400; text-decoration: none; font-size: 2rem; line-height: 1.1812500000000001rem; height: 45px; width: 45px; text-align: center; padding: 0rem; border: 1px solid; border-radius: 50%; display: -webkit-inline-box; display: -ms-inline-flexbox; display: flex; justify-content: center; -webkit-box-align: center; -ms-flex-align: center; align-items: center; position: absolute; right: 7px; bottom: 6.8% } .footer-email form { position: relative } .footer-email input:not([type="radio"]):not([type="checkbox"]):not([type="file"]):not([type="submit"]):not([type="button"]) { border-radius: 40px; background: #012E41; border-color: #012E41; color: #f9f9f9; box-shadow: 0 3px 20px #0000002e } .footer-email .hs-error-msgs { position: absolute } .footer-email input[type=submit].hs-button.primary { background: #ffffff !important; 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href="https://www.isg-research.net/customerexperience" class="minimal-mobile-menu-link"><span>Customer Experience</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/agentmanagement" class="minimal-mobile-menu-link"><span>Agent Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/contactcenter" class="minimal-mobile-menu-link"><span>Contact Center</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/customerexperiencemanagement" class="minimal-mobile-menu-link"><span>Customer Experience Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/fieldservice" class="minimal-mobile-menu-link"><span>Field Service</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/intelligentselfservice" class="minimal-mobile-menu-link"><span>Intelligent Self-Service</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/customerexperience/voiceofthecustomer" class="minimal-mobile-menu-link"><span>Voice of the Customer</span></a></span> </li> </ul> </li> <li class="minimal-has-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/digitalbusiness" class="minimal-mobile-menu-link"><span>Digital Business</span></a></span> <ul class="minimal-mobile-menu-submenu level-3"> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/digital-applications" class="minimal-mobile-menu-link"><span>Digital Applications</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/digitalcommunications" class="minimal-mobile-menu-link"><span>Digital Communications</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/digital-intelligence" class="minimal-mobile-menu-link"><span>Digital Intelligence</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/digital-operations" class="minimal-mobile-menu-link"><span>Digital Operations</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/experiencemanagement" class="minimal-mobile-menu-link"><span>Experience Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/generative-ai" class="minimal-mobile-menu-link"><span>Generative AI</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/performancemanagement" class="minimal-mobile-menu-link"><span>Performance Management</span></a></span> </li> <li class="minimal-no-mobile-submenu minimal-mobile-menu-item hs-skip-lang-url-rewrite"> <span><a href="https://www.isg-research.net/focus/digitalbusiness/sustainabilityandesg" class="minimal-mobile-menu-link"><span>Sustainability &amp; 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 &amp; 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 &amp; 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 &amp; 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 &amp; 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 &amp; 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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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="custom-banner" style="background-image: -moz-linear-gradient(top, rgba(0,0,0,0.57), rgba(0,0,0,0.57)), url(''); background-image: -webkit-linear-gradient(top, rgba(0,0,0,0.57), rgba(0,0,0,0.57)), url(''); background-image: -ms-linear-gradient(top, rgba(0,0,0,0.57), rgba(0,0,0,0.57)), url(''); background-image: linear-gradient(top, rgba(0,0,0,0.57), rgba(0,0,0,0.57)), url('');"> <div class="custom-banner-content"> <h1><img class="analyst-header-photo" src="https://jefforr.isg-research.net/hubfs/_images/_team/profile_vr_jeff_orr_circle_292x292.png" style="padding: 10px; "><br>David Menninger's Analyst Perspectives</h1> </div> </div> --> <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> <!-- <h1><span id="hs_cos_wrapper_name" class="hs_cos_wrapper hs_cos_wrapper_meta_field hs_cos_wrapper_type_text" style="" data-hs-cos-general-type="meta_field" data-hs-cos-type="text" >David Menninger</span>123tests</h1>--> </div> </div> </div> </div> <div class="content-wrapper-listing blog-single"> <div class="blog-content-wrapper"> <div> <!-- class="blog-index" --> <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> --> <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&amp;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&amp;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&amp;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&amp;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&amp;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&amp;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&amp;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 &amp; Data</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-data-events">Streaming Data &amp; 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/gooddatas-embedded-analytics-democratizes-data-driven-decisions">GoodData’s Embedded Analytics Democratizes Data-Driven Decisions</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 August 2023 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png?width=200&amp;name=GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png?width=100&amp;name=GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png?width=200&amp;name=GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png?width=300&amp;name=GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png?width=400&amp;name=GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png?width=500&amp;name=GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png?width=600&amp;name=GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>The current market landscape of data and analytics is undergoing rapid evolution, presenting organizations with a wide array of challenges and opportunities. As data sources and warehouses steadily migrate to the cloud, a significant number of organizations still depend on conventional tools. This reliance on legacy systems hinders the seamless accessibility and adoption of analytics and business intelligence within business processes. Organizations are increasingly turning to embedded...</p> </div> <a href="https://davidmenninger.isg-research.net/gooddatas-embedded-analytics-democratizes-data-driven-decisions"><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>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-analytics">Streaming Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</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/sigma-computing-makes-cloud-analytics-more-accessible">Sigma Computing Makes Cloud Analytics More Accessible</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 April 2023 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png?width=200&amp;name=Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png?width=100&amp;name=Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png?width=200&amp;name=Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png?width=300&amp;name=Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png?width=400&amp;name=Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png?width=500&amp;name=Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png?width=600&amp;name=Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Organizations are becoming increasingly aware of the potential value that can be gained by processing big data. As data sources grow, it becomes important to have tools and methods to effectively process, analyze and visualize this information from disparate systems and warehouses.</p> </div> <a href="https://davidmenninger.isg-research.net/sigma-computing-makes-cloud-analytics-more-accessible"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/business-intelligence-2">business intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/embedded-analytics">embedded analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-analytics">Streaming 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/sisense-is-sensible-for-embedded-analytics-and-bi">Sisense is Sensible for Embedded Analytics and BI</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-research.net/author/david-menninger"> David Menninger </a> on <span class="post-date">07 December 2022 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png?width=200&amp;name=AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png?width=100&amp;name=AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png?width=200&amp;name=AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png?width=300&amp;name=AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png?width=400&amp;name=AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png?width=500&amp;name=AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png?width=600&amp;name=AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Embedded business intelligence (BI) continues to transform the business landscape, enabling organizations to quickly interpret data and convert it into actionable insights. It allows organizations to extract information in real time and answer wide-ranging business questions. Embedding analytics helps tackle the issue of extracting information from data which is a time-consuming process. Our research shows organizations spend more time cleaning and optimizing data for analysis rather than...</p> </div> <a href="https://davidmenninger.isg-research.net/sisense-is-sensible-for-embedded-analytics-and-bi"><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>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/natural-language-processing">natural language processing</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-analytics">Streaming Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</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/celonis-improves-business-processes-with-process-mining">Celonis Improves Business Processes with Process Mining</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">14 October 2022 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png?width=200&amp;name=AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png?width=100&amp;name=AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png?width=200&amp;name=AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png?width=300&amp;name=AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png?width=400&amp;name=AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png?width=500&amp;name=AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png?width=600&amp;name=AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>As I recently pointed out, <a href="https://davidmenninger.ventanaresearch.com/process-mining-improves-business-processes" rel="noopener" target="_blank" style="text-decoration: none;">process mining</a> has emerged as a pivotal technology for data-driven organizations to discover, monitor and improve processes through use of real-time event data, transactional data and log files. With recent advancements, process mining has become more efficient at discovering insights in complex processes using algorithms and visualizations. Organizations use it to better understand the current state of systems and business processes. It is also used to enable <a href="/the-digital-awakening-of-business-process-intelligence" rel="noopener" target="_blank" style="text-decoration: none;">...</a></p> </div> <a href="https://davidmenninger.isg-research.net/celonis-improves-business-processes-with-process-mining"><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/process-mining">Process Mining</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-analytics">Streaming Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</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/palantir-operationalizes-analytics-and-data-for-actions-and-decisions">Palantir Operationalizes Analytics and Data for Actions and Decisions</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">26 August 2022 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png?width=200&amp;name=AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png?width=100&amp;name=AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png?width=200&amp;name=AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png?width=300&amp;name=AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png?width=400&amp;name=AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png?width=500&amp;name=AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png?width=600&amp;name=AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Organizations are managing and analyzing large datasets every day, identifying patterns and generating insights to inform decisions. This can provide numerous benefits for an organization, such as improved operational efficiency, cost optimization, fraud detection, competitive advantage and enhanced business processes. By bringing the right, actionable data to the right user, organizations can potentially speed up processes and make more effective operational decisions.</p> </div> <a href="https://davidmenninger.isg-research.net/palantir-operationalizes-analytics-and-data-for-actions-and-decisions"><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>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/internet-of-things">Internet of Things</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-analytics">Streaming Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</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/expanding-the-analytics-continuum-from-analysis-to-action">Expanding the Analytics Continuum: From Analysis to Action</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">02 August 2022 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png?width=200&amp;name=AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png?width=100&amp;name=AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png?width=200&amp;name=AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png?width=300&amp;name=AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png?width=400&amp;name=AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png?width=500&amp;name=AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png?width=600&amp;name=AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>I often use the term “analytics” to refer to a broad set of capabilities, deliberately broader than business intelligence. In this Perspective, I’d like to share what decision-makers should consider as they evaluate the range of analytics requirements for their organization.</p> </div> <a href="https://davidmenninger.isg-research.net/expanding-the-analytics-continuum-from-analysis-to-action"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/natural-language-processing">natural language processing</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 &amp; Data</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</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/zoho-unifies-data-and-analytics">Zoho Unifies Data and 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">07 July 2022 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png?width=200&amp;name=AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png?width=100&amp;name=AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png?width=200&amp;name=AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png?width=300&amp;name=AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png?width=400&amp;name=AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png?width=500&amp;name=AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png?width=600&amp;name=AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Organizations are continuously increasing the use of analytics and business intelligence to turn data into meaningful and actionable insights. Our <a href="https://www.ventanaresearch.com/benchmark/analytics/analytics_and_data/research_report/2022" rel="noopener" target="_blank" style="text-decoration: none;">Analytics and Data Benchmark Research</a> shows some of the benefits of using analytics: Improved efficiency in business processes, improved communication and gaining a competitive edge in the market top the list. With a unified BI system, organizations can have a comprehensive view of all organizational data to better manage processes and identify...</p> </div> <a href="https://davidmenninger.isg-research.net/zoho-unifies-data-and-analytics"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-research.net/topic/business-intelligence-3">business intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/embedded-analytics">embedded analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/data-governance">Data Governance</a>, <a href="https://davidmenninger.isg-research.net/topic/data-management">Data Management</a>, <a href="https://davidmenninger.isg-research.net/topic/natural-language-processing">natural language processing</a>, <a href="https://davidmenninger.isg-research.net/topic/data-operations">data operations</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-analytics">Streaming Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-data-events">Streaming Data &amp; Events</a>, <a href="https://davidmenninger.isg-research.net/topic/operational-data-plaftforms">operational data plaftforms</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</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/denodo-advancing-data-virtualization-in-the-cloud">Denodo Advancing Data Virtualization in the Cloud</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">28 April 2022 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png?width=200&amp;name=AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png?width=100&amp;name=AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png?width=200&amp;name=AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png?width=300&amp;name=AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png?width=400&amp;name=AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png?width=500&amp;name=AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png?width=600&amp;name=AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Organizations have been using data virtualization to collect and integrate data from various sources, and in different formats, to create a single source of truth without redundancy or overlap, thus improving and accelerating decision-making giving them a competitive advantage in the market. Our research shows that data virtualization is popular in the big data world. One-quarter (27%) of participants in our <a href="https://www.ventanaresearch.com/dynamic_insights/big_data/data_lakes/survey" rel="noopener" target="_blank">Data Lake Dynamic Insights</a> Research reported they were currently using data...</p> </div> <a href="https://davidmenninger.isg-research.net/denodo-advancing-data-virtualization-in-the-cloud"><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>, <a href="https://davidmenninger.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-analytics">Streaming Analytics</a>, <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning</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/dont-rely-on-dashboards-for-real-time-analytics">Don’t Rely on Dashboards for 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">31 March 2022 </span> </div> <!-- <hr> --> <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png?width=200&amp;name=AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png" width="200" !important: srcset="https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png?width=100&amp;name=AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png?width=200&amp;name=AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png?width=300&amp;name=AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png 300w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png?width=400&amp;name=AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png 400w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png?width=500&amp;name=AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png 500w, https://davidmenninger.isg-research.net/hs-fs/hubfs/AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png?width=600&amp;name=AP_DM_Don%E2%80%99t%20Rely%20on%20Dashboards%20for%20Real-Time%20Analytics.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>I have <a href="https://davidmenninger.ventanaresearch.com/historical-databases-becoming-a-thing-of-the-past" style="text-decoration: none;">written previously</a> that the world of data and analytics will become more and more centered around real-time, streaming data. Data is created constantly and increasingly is being collected simultaneously. Technology advances now enable organizations to process and analyze information as it is being collected to respond in real time to opportunities and threats. Not all use cases require real-time analysis and response, but many do, including multiple use cases that can improve customer...</p> </div> <a href="https://davidmenninger.isg-research.net/dont-rely-on-dashboards-for-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/internet-of-things">Internet of Things</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 &amp; Data</a>, <a href="https://davidmenninger.isg-research.net/topic/streaming-data-events">Streaming Data &amp; 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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 class="about-author-sec row-fluid"> <div class="span12"> <h3 style="color: var(--light_blue);">About the Analyst</h3> <h4>Quincy Valencia</h4> <p>Quincy brings over two decades of experience in human capital management covering the span of engaging the workforce and value of people in the organization. </p><p style="text-align: center;"><a class="author-link fancy-btn" href="https://quincyvalencia.isg-research.net/author/quincy-valencia">Read more</a></p> </div> </div> --> <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> <!--start row--> <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&amp;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&amp;name=Menninger.David%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&amp;name=Menninger.David%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=150&amp;name=Menninger.David%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=200&amp;name=Menninger.David%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=250&amp;name=Menninger.David%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=300&amp;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&amp;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&amp;name=Orr.Jeff.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&amp;name=Orr.Jeff.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=150&amp;name=Orr.Jeff.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=200&amp;name=Orr.Jeff.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=250&amp;name=Orr.Jeff.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=300&amp;name=Orr.Jeff.Circle.png 300w" sizes="(max-width: 100px) 100vw, 100px"> <h5 class="analyst_name">Jeff Orr</h5> </a> </div> </div> <!--end row--> <!--start row--> <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&amp;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&amp;name=Dawson.Keith%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&amp;name=Dawson.Keith%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=150&amp;name=Dawson.Keith%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=200&amp;name=Dawson.Keith%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=250&amp;name=Dawson.Keith%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=300&amp;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&amp;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&amp;name=Smith.Mark%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&amp;name=Smith.Mark%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=150&amp;name=Smith.Mark%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=200&amp;name=Smith.Mark%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=250&amp;name=Smith.Mark%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=300&amp;name=Smith.Mark%20Pic.Circle.png 300w"> <h5 class="analyst_name">Mark Smith</h5> </a> </div> </div> <!--end row--> <!--start row--> <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&amp;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&amp;name=Aslett.Matt%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&amp;name=Aslett.Matt%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=150&amp;name=Aslett.Matt%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=200&amp;name=Aslett.Matt%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=250&amp;name=Aslett.Matt%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=300&amp;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&amp;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&amp;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&amp;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&amp;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&amp;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&amp;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&amp;name=profile_vr_matthew_brown_circle_900x900.png 300w"> <h5 class="analyst_name">Matthew Brown</h5> </a> </div> </div> <!--end row--> <!--start row--> <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&amp;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&amp;name=Kugel.Robert%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&amp;name=Kugel.Robert%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=150&amp;name=Kugel.Robert%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=200&amp;name=Kugel.Robert%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=250&amp;name=Kugel.Robert%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=300&amp;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&amp;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&amp;name=Hurrell.Stephen%20Pic.Circle.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&amp;name=Hurrell.Stephen%20Pic.Circle.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=150&amp;name=Hurrell.Stephen%20Pic.Circle.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=200&amp;name=Hurrell.Stephen%20Pic.Circle.png 200w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=250&amp;name=Hurrell.Stephen%20Pic.Circle.png 250w, https://davidmenninger.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=300&amp;name=Hurrell.Stephen%20Pic.Circle.png 300w"> <h5 class="analyst_name">Stephen Hurrell</h5> </a> </div> </div> <!--end row--> <!--start row--> <div class="row-fluid"> <!-- <div class="span6" style="text-align: center;"> <a href="https://robertkugel.isg-research.net"> <img class="analyst_img" style="display:inline;" src="https://blog.isg-research.net/hs-fs/hubfs/Images/Analyst_Photos/Rob_2016_Circle_Zoomed.png?width=100&amp;name=Rob_2016_Circle_Zoomed.png" alt="Robert Kugel" width="100" style="width: 100px;" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px"> <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="display:inline;" src="https://blog.isg-research.net/hs-fs/hubfs/Images/Analyst_Photos/Stephen-Hurrell-Bio-Photo-Circle-1-1.png?width=100&amp;name=Stephen-Hurrell-Bio-Photo-Circle-1-1.png" alt="Stephen Hurrell" width="100" style="width: 100px;" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px"> <h5 class="analyst_name">Stephen Hurrell</h5> </a> </div> --> <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&amp;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&amp;name=ISG_Bug_Reverse_Transparent.png 50w, https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=100&amp;name=ISG_Bug_Reverse_Transparent.png 100w, https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=150&amp;name=ISG_Bug_Reverse_Transparent.png 150w, https://davidmenninger.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=200&amp;name=ISG_Bug_Reverse_Transparent.png 200w, 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dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2021/02">February 2021 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2021/01">January 2021 <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2020/11">November 2020 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2020/10">October 2020 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2020/05">May 2020 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2020/04">April 2020 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2020/03">March 2020 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2020/02">February 2020 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/09">September 2019 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/08">August 2019 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/07">July 2019 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/06">June 2019 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/05">May 2019 <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/04">April 2019 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/03">March 2019 <span class="filter-link-count" dir="ltr">(9)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/02">February 2019 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2019/01">January 2019 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/12">December 2018 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/11">November 2018 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/10">October 2018 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/09">September 2018 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2018/02">February 2018 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/12">December 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/11">November 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/09">September 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/08">August 2017 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/07">July 2017 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/06">June 2017 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/05">May 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/04">April 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/03">March 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/02">February 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2017/01">January 2017 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/12">December 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/11">November 2016 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/10">October 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/09">September 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/08">August 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/07">July 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/05">May 2016 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/04">April 2016 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/03">March 2016 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2016/02">February 2016 <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2012/03">March 2012 <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2012/02">February 2012 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2012/01">January 2012 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/12">December 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/11">November 2011 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/10">October 2011 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/09">September 2011 <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/08">August 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/07">July 2011 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/06">June 2011 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/05">May 2011 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/04">April 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/03">March 2011 <span class="filter-link-count" dir="ltr">(7)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/02">February 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2011/01">January 2011 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2010/12">December 2010 <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2010/11">November 2010 <span class="filter-link-count" dir="ltr">(12)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/archive/2010/06">June 2010 <span class="filter-link-count" dir="ltr">(1)</span></a> </li> </ul> <a class="filter-expand-link" href="#">see all</a> </div> </div> </span> <span id="hs_cos_wrapper_post_filter" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_post_filter" style="" data-hs-cos-general-type="widget" data-hs-cos-type="post_filter"><div class="block"> <h3>Posts by Topic</h3> <div class="widget-module"> <ul> <li> <a href="https://davidmenninger.isg-research.net/topic/ai">AI <span class="filter-link-count" dir="ltr">(11)</span></a> </li> <li> <a href="https://davidmenninger.isg-research.net/topic/ai-and-machine-learning">AI and Machine Learning <span class="filter-link-count" dir="ltr">(95)</span></a> </li> <li> <a href="https://davidmenninger.isg-research.net/topic/alteryx">alteryx <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li> <a href="https://davidmenninger.isg-research.net/topic/alteryx-inspire">Alteryx Inspire <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li> <a href="https://davidmenninger.isg-research.net/topic/analytic-data-platforms">analytic data platforms <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/analytic-operations">Analytic Operations <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/analytics">Analytics <span class="filter-link-count" dir="ltr">(216)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/analytics-data">Analytics &amp; Data <span class="filter-link-count" dir="ltr">(40)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/artificial-intelligence">Artificial intelligence <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/augmented-analytics">Augmented Analytics <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/bi-platform">BI platform <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/big-data">Big Data <span class="filter-link-count" dir="ltr">(65)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/blockchain">blockchain 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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" 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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 <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/embedded-analytics">embedded analytics <span class="filter-link-count" dir="ltr">(65)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/emc">EMC <span 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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 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dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/ibm">IBM <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/ibm-spss">IBM SPSS <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/ibm-watson">IBM Watson <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/in-memory">In-memory <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/in-memory-computing">In-Memory Computing <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/inetsoft">InetSoft <span 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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 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href="https://davidmenninger.isg-research.net/topic/karmasphere">Karmasphere <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/kognitio">Kognitio <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/kxen">KXEN <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/location-intelligence">Location Intelligence <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/looker">looker <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-data">Machine data <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-learning">Machine Learning <span class="filter-link-count" dir="ltr">(11)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-learning-and-cognitive-computing">Machine Learning and Cognitive Computing <span class="filter-link-count" dir="ltr">(7)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-learning-digital-technology">Machine Learning Digital Technology <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/machine-learning-operations">Machine Learning Operations <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mapr">MapR <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li 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href="https://davidmenninger.isg-research.net/topic/mobile-computing">mobile computing <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobile-intelligence">Mobile Intelligence <span class="filter-link-count" dir="ltr">(3)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobile-technology">Mobile Technology <span class="filter-link-count" dir="ltr">(18)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mobility">Mobility <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/model-building-and-large-language-models">Model Building and Large Language Models <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/mpp">MPP <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/natural-language">Natural Language <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/natural-language-processing">natural language processing <span class="filter-link-count" dir="ltr">(46)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/natural-language-query">Natural Language Query <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/netapp">NetApp <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/netezza">Netezza <span class="filter-link-count" 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href="https://davidmenninger.isg-research.net/topic/partner-management">partner management <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/pentaho">Pentaho <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/performance-management">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/planning">Planning <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/predictive-analytics">Predictive Analytics <span class="filter-link-count" dir="ltr">(26)</span></a> </li> <li style="display:none;"> <a href="https://davidmenninger.isg-research.net/topic/predictive-planning">Predictive Planning <span 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src="https://davidmenninger.isg-research.net/hs-fs/hub/2035844/hub_generated/module_assets/90531062927/1702386872146/module_90531062927_Header-Global.min.js"></script> <script type="application/ld+json"> { "@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": "GoodData’s Embedded Analytics Democratizes Data-Driven Decisions", "mainEntityOfPage": "https://davidmenninger.isg-research.net/gooddatas-embedded-analytics-democratizes-data-driven-decisions", "datePublished": "17/08/2023", "dateModified": "17/08/2023", "articleBody": "The current market landscape of data and analytics is undergoing rapid evolution, presenting organizations with a wide array of challenges and opportunities. As data sources and warehouses steadily migrate to the cloud, a significant number of organizations still depend on conventional tools. This reliance on legacy systems hinders the seamless accessibility and adoption of analytics and business intelligence within business processes. Organizations are increasingly turning to embedded analytics to address this challenge, enhancing the user experience, improving efficiency and democratizing data access. Our Analytics and Data Benchmark Research shows that three-quarters of organizations consider embedded analytics important. By integrating analytics directly into applications and workflows, organizations enable teams to easily access and analyze data from within their familiar work environments without switching between multiple applications. GoodData is a cloud-based analytics and BI platform that enables organizations to capture and load data from a variety of sources. Users can construct metrics, generate reports and create interactive dashboards. Its embedded analytics allows workers to integrate analytics into various applications and workflows. GoodData has offered cloud analytics and BI software for over a decade. Its platform enables users to explore, analyze and derive insights from data without relying on IT teams. Users can build data pipelines and design logical data models, facilitating the delivery of tailored and reusable analytic solutions. Features include: GoodData Cloud, a hosted cloud application available on Amazon Web Services for building and delivering multitenant analytics on top of an organization’s existing data sources. It enables users to submit queries in Multidimensional Analytical Query Language or through custom applications. The platform utilizes metadata and a caching mechanism to optimize query performance and the volume of data transferred between data storage and the analytical engine. Analytical Designer, enabling users to build visualizations and use self-service data discovery. GoodData.UI, a TypeScript framework that allows users to build analytical web applications. It consists of multiple libraries ‒ from low-level REST application programming interface clients up to visualization libraries that deliver React-based components to render different types of charts and tables. GoodData.CN, an analytics platform that can be deployed in a public cloud, on-premises or on a laptop. It is focused on the semantic layer and offers a multitenant environment. The platform also enables users to create interactive charts and dashboards using its drag-and-drop interface. GoodData enables users to query data sources directly without copying or moving data, ensuring decisions are based on real-time information. It offers services to various industries, including software companies, e-commerce/retail, financial services, insurance, industrial and healthcare. The platform connects to various data warehouses and databases, including Snowflake, Amazon Redshift, Azure SQL, Databricks, Google BigQuery, Microsoft SQL Server, PostgreSQL and Synapse. Our market assessment suggests that by 2026, more than two-thirds of line-of-business personnel will have immediate access to cross-functional analytics embedded in activities and processes helping to make operational decision-making more efficient and effective. GoodData’s analytics platform enables workers to build sophisticated data products for customers and business partners. It offers many customization options and developer tools for engineering teams to build applications on top of the GoodData platform. Developers can also automate deployment, testing and repetitive tasks with its open-source developer tools. GoodData recently introduced its data transformation tool ‒ Last Mile ETL, which enables users to perform data transformations within the analytics platform. It eliminates the need for context-switching between the extract, load and transform or extract, transform and load pipeline and analytics, streamlining the data transformation process. It offers built-in data visualization types and the flexibility to incorporate charts from external visualization libraries such as D3, Chart.js, FusionCharts and Google Charts. GoodData recently partnered with Arria to provide natural language capabilities. With this integration, GoodData can maximize Arria’s technology to provide self-service narrative insights to supplement visualizations and tables of data. To further improve and expand its products and services, GoodData should continue enhancing its data integration and artificial intelligence capabilities and complete its plans to support Google Cloud Platform and Microsoft Azure for additional deployment options. As the market for decision intelligence grows, GoodData could expand its analytical capabilities or partnerships to include driver-based planning. By incorporating embedded analytics into everyday work environments, GoodData allows more of the workforce to make data-driven decisions. GoodData's cloud-based approach, flexibility and focus on customization and scalability position it to support organizations in the journey to improve decision-making and operational efficiency. We recommend that organizations seeking a cloud-based analytics and BI platform with embeddable analytics capabilities consider GoodData. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/GoodDatas_Embedded_Analytics_Democratizes_Data-Driven_Decisions.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": "Sigma Computing Makes Cloud Analytics More Accessible", "mainEntityOfPage": "https://davidmenninger.isg-research.net/sigma-computing-makes-cloud-analytics-more-accessible", "datePublished": "13/04/2023", "dateModified": "13/04/2023", "articleBody": "Organizations are becoming increasingly aware of the potential value that can be gained by processing big data. As data sources grow, it becomes important to have tools and methods to effectively process, analyze and visualize this information from disparate systems and warehouses. Our Analytics and Data Benchmark Research shows that the majority of the workforce in an organization is not using analytics. Part of the challenge in democratizing data and analytics is that accessing insights usually includes multiple steps in between. Processing big data often requires extensive IT support and specialized expertise, making it difficult for non-technical users to access and analyze data. Another major challenge is difficulty in accessing data sources and bringing data together in one place. Sigma Computing is a Silicon Valley-based company founded in 2014. It offers a self-service cloud analytics and business intelligence platform. Its data exploration tool is based on a spreadsheet-like interface that anyone in the organization can use to analyze data from multiple data sources and get insights from their cloud data warehouse. Users can study very large data sets, create new metrics and perform what-if analysis interactively. It also offers collaborative features, enabling multiple users to work on the same project simultaneously and share insights in real time. Sigma automates SQL query writing, enabling users to generate their own analysis, reporting, visualizations and dashboards from multiple data sources without writing code. The platform has built-in connections to link various data sources including Snowflake, Databricks, Google Big Query and PostgreSQL. Users can perform ad hoc queries to live data, find insights and make data-driven business decisions without having to pre-define drill paths. Sigma offers its software to a wide range of organizations across different industries, including finance, manufacturing, retail, healthcare and e-commerce. For business users, it provides a codeless experience to analyze data and discover insights. The platform also offers templates and data warehouse views to enable users to model and analyze the data from within the platform. Sigma recently introduced a new feature called Live Edit which enables multiple users to see the same screen as it is being created and edited, making it easier to collaborate in real time on dashboards, metrics and data stories. Sigma Computing also offers embedded analytics capabilities that enables organizations to incorporate analytics in products and portals. Embedding analytics into other applications and business processes addresses several key issues I have written about previously that often become barriers to adoption. In addition, embedding analytics can help achieve more self-service within an organization. In a constantly changing business environment, self-service data exploration capabilities help organizations remain agile and competitive and make data-driven decisions quickly and effectively. Sigma offers a wide range of analytics and BI capabilities and is growing in the cloud analytics market. The company could build on its spreadsheet-style interface by adding more what-if capabilities, which are lacking among many vendors in this market. Cloud analytics platforms enable organizations to gain valuable insights and make data-driven decisions that improve operations, reduce costs and increase competitiveness. Being a cloud-native application, Sigma offers the flexibility to scale to many users on the same instance. Its spreadsheet-like interface and its ability to embed charts and graphs on other platforms enables organizations to provide their team and customers easy access to data and analytics. Sigma also supports many compliance standards including the California Consumer Privacy Act, General Data Protection Regulation and the Health Insurance Portability and Accountability Act. It can be deployed on Amazon Web Services and Google Cloud Platform. Organizations looking for a cloud-native analytics platform with a spreadsheet-style interface that works with multiple data sources and warehouses should consider Sigma Computing. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/Sigma_Computing_Makes_Cloud_Analytics_More_Accessible.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": "Sisense is Sensible for Embedded Analytics and BI", "mainEntityOfPage": "https://davidmenninger.isg-research.net/sisense-is-sensible-for-embedded-analytics-and-bi", "datePublished": "07/12/2022", "dateModified": "07/12/2022", "articleBody": "Embedded business intelligence (BI) continues to transform the business landscape, enabling organizations to quickly interpret data and convert it into actionable insights. It allows organizations to extract information in real time and answer wide-ranging business questions. Embedding analytics helps tackle the issue of extracting information from data which is a time-consuming process. Our research shows organizations spend more time cleaning and optimizing data for analysis rather than creating insights. On top of that, they are adding more data sources and information systems which in turn introduces more complexity. Our Analytics and Data Benchmark Research shows that organizations face various challenges with analytics and BI. More than one-third of participants (35%) responded that they find it hard to integrate analytics and BI with business processes and connect to multiple data sources. By embedding analytics and BI into business processes and workflows, organizations can enable users to make critical decisions fast, enhancing overall business agility. Sisense is a BI software company that focuses on enabling organizations to embed analytics in business applications and workflows. It offers a scalable platform with cloud agnostic deployment and integration capabilities with Amazon Web Services (AWS), Snowflake, Google and Microsoft, among others. Sisense offers three solutions in its Sisense Fusion Platform — Sisense Fusion Embed, Sisense Infusion Apps, and Sisense Fusion Analytics. The Sisense Fusion Platform is an artificial intelligence (AI)-enabled, analytics cloud platform that offers the ability to embed analytics into customer-facing applications. Users of different skill levels can analyze data and then infuse customized experiences into different workflows and processes. Sisense Fusion Embed is its embedding solution that infuses AI-driven analytics into products and business applications. Users can use its code-free tools for analysis and can augment analytics with AI and machine learning (ML) without requiring extensive IT support. Sisense Infusion Apps enables users to use natural language query (NLQ) to fetch, analyze and deliver insights from within productivity tools like Microsoft Office 365, Microsoft Teams, Google Workspace or Slack. It can be deployed in the cloud or on-premises, with a single tenant or multi-tenant architecture, and features end-to-end governance and security that can be automated via APIs. By bringing self-service and embedded analytics to individuals, organizations can increase the value of data and enhance overall productivity. Sisense Fusion Analytics enables business users to integrate BI into workflows and business tools such as Slack, Salesforce, Google Docs and Google Sheets. Its platform also enables users to collaborate around data and BI. Organizations can use Sisense to import data from several data sources and visualize it using dashboards. Additionally, Sisense uses AI for automated data preparation and delivery of insights. It can also provide forecasts based on historical data, enabling nontechnical users to predict business outcomes, track changes to critical metrics and make decisions based on new insights. As I’ve written previously, AI-driven augmented analytics can give users faster answers and actionable insights into their business metrics. By automating data preparation, insight discovery and sharing, organizations can speed up the decision-making process, improve the state of analytics and gain a competitive edge in the market. Sisense should continue to invest in its integration capabilities and add in more business partners to expand the portfolio of software and tools it can connect and integrate with. I recommend that organizations looking to embed analytics into business applications, processes and workflows evaluate Sisense. It offers multiple embed options and libraries, including iFrames, Embed SDK and Sisense JS. It enables users to combine data and uncover insights in a single interface without scripting, coding or extensive IT assistance. By augmenting intelligence in business processes, organizations can automate AI/ML analyses and provide guided or assisted features within data and analytics products. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/AP_DM_Sisense_is_Sensible_for_Embedded_Analytics_and_BI.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": "Celonis Improves Business Processes with Process Mining", "mainEntityOfPage": "https://davidmenninger.isg-research.net/celonis-improves-business-processes-with-process-mining", "datePublished": "14/10/2022", "dateModified": "14/10/2022", "articleBody": "As I recently pointed out, process mining has emerged as a pivotal technology for data-driven organizations to discover, monitor and improve processes through use of real-time event data, transactional data and log files. With recent advancements, process mining has become more efficient at discovering insights in complex processes using algorithms and visualizations. Organizations use it to better understand the current state of systems and business processes. It is also used to enable business process intelligence and improvement in any function or industry using events and activity models for data-driven decision-making. We assert that through 2024, 1 in 4 organizations will look to streamline their operations by exploring process mining to optimize workflow and business processes. Celonis is a process mining software company that offers an execution management system platform to enhance business performance. It uses data, intelligence and automated actions to locate and fix process issues in enterprise systems. Its platform enables users to visualize, audit and analyze processes to understand pain points and improve business operations. Celonis Studio is its app-building solution that enables users and third-party developers to create execution applications on its EMS platform. Celonis extracts process data from a variety of systems, including on-premises or cloud enterprise resource planning systems, customer relationship management systems, data warehouses, productivity tools and desktop activities. It offers over 3,000 unique source systems and 100-plus pre-built process connectors. Its platform automates data extraction and transformation, and offers task-mining capabilities to collect desktop user data by capturing user clicks and application actions. It also offers the capability to plan and simulate process changes to define and test various strategies before final implementation. Earlier this year, Celonis announced the acquisition of Process Analytics Factory, which provides process-mining insights for Microsoft Power BI. With this acquisition, Celonis plans to enable Microsoft Power Platform users to employ Celonis EMS for process mining, automation and collaboration. It has become a priority for organizations to continuously optimize and automate processes to achieve maximum efficiency. Process mining enables users to surface the bottlenecks that create barriers to productivity and profitability. It offers a more granular way to identify deviations and aberrations, course-correcting them in real-time. Celonis works as a layer on top of existing systems, so organizations can utilize current technology investments. It enables organizations to gain real-time visibility into how processes are running and how they can be improved. Process mining supports numerous use cases, including process automation and digital transformation. Organizations looking to improve business processes and efficiency should evaluate Celonis. It provides a comprehensive set of tools for business execution and process improvement, including automation, workflows and simulation. Its EMS combines real-time data and process intelligence to enable organizations to understand process pain points and take targeted action. By identifying inefficiencies in business functions, organizations can take appropriate actions to improve performance and remove process gaps. We have recently launched a Dynamic Insights research survey on process mining, designed for data and technology professionals. It provides an evaluation of your organization’s efforts and our prescriptive guidance, based on your specific responses. Take the survey here. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/AP_DM_Celonis_Improves_Business_Processes_with_Process_Mining.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": "Palantir Operationalizes Analytics and Data for Actions and Decisions", "mainEntityOfPage": "https://davidmenninger.isg-research.net/palantir-operationalizes-analytics-and-data-for-actions-and-decisions", "datePublished": "26/08/2022", "dateModified": "26/08/2022", "articleBody": "Organizations are managing and analyzing large datasets every day, identifying patterns and generating insights to inform decisions. This can provide numerous benefits for an organization, such as improved operational efficiency, cost optimization, fraud detection, competitive advantage and enhanced business processes. By bringing the right, actionable data to the right user, organizations can potentially speed up processes and make more effective operational decisions. Many organizations are taking steps to advance current technology and improve the analytics life cycle. Decision intelligence is an emerging discipline that connects decision support, decision management and big, complex systems. Fields such as financial services, healthcare, and supply chain benefit from using data and artificial intelligence to automate and accelerate the decision-making process. By 2024, we assert that one-third of organizations will adopt an analytic operations approach similar to - and integrated with - data operations processes to enhance responsiveness and agility. Palantir is a data analytics software company that offers a suite of applications for integrating, analyzing and visualizing data to enable decision intelligence. It supports various datasets, including structured, unstructured, relational, temporal and geospatial. Palantir went public in 2020 and is well known for its work with the government and law enforcement agencies. Palantir offers three software platforms – Palantir Gotham, Palantir Foundry and Palantir Apollo. Gotham and Foundry offer the capability to transform big data into an integrated dataset and surface insights. Palantir Apollo is its continuous delivery system that powers Gotham and Foundry. It enables organizations to manage and continuously deploy the software wherever it’s needed. Data projects often run into roadblocks because the steps and methods used to build data pipelines are difficult to understand and recreate. Our Analytics and Data Benchmark Research shows that data preparation, reviewing data for quality issues and waiting for data and information are some of the most time-consuming processes. By having all the data in one platform, organizations can better manage the processes and data pipelines. Foundry is Palantir’s fully managed cloud-computing platform that offers the capability to collect data from multiple sources, analyze it and create insights. It enables users to experiment and test new ideas. Palantir Foundry was initially focused on public-sector customers such as the U.S. Department of Defense, but has since evolved to serve numerous companies in the private sector. Organizations can use Foundry to collect data from databases, internet of things devices and other systems. Palantir Gotham is broadly used in government functions and the financial services industry. It can enable organizations to find patterns in datasets and also facilitate the hand-off between analysts and operational users, enabling operators to plan and execute real-world responses to threats that have been identified within the platform. Palantir recently announced a multi-year partnership with Google Cloud to support digital transformations and accelerate operational analytics in commercial industries, including retail, financial services and supply chain and logistics. With this partnership, Palantir’s Foundry platform is now available on Google Cloud and Google Cloud Marketplace, allowing organizations to utilize its numerous services to enhance data analytics operations. This enables organizations to gain new data integration, management and business intelligence capabilities to synthesize data and address operational problems. Users can also use Foundry’s capabilities with Google Cloud Cortex Framework for data analysis and management on Google Cloud. In addition, Foundry can be used with Google BigQuery. Organizations can also bring SAP-based data into the Cortex Framework through its reference architecture so it can be analyzed and managed on Google Cloud. Palantir Foundry was selected for our 14th Annual Ventana Research Overall Digital Innovation Award in 2021, and written about by our CEO and Chief Research Officer Mark Smith. Organizations are running on multiple clouds and have to maintain systems in multiple locations. Palantir Apollo is a standalone platform that runs as a layer between its applications and underlying infrastructure. It can manage production software in various environments, including private cloud, Google Cloud Platform, Amazon Web Services, Microsoft Azure and hybrid cloud configurations. Apollo offers the ability to apply the constraints that are declared by developers and other stakeholders when performing environment updates. The Apollo orchestration engine is the core element that ensures these constraints and rules are satisfied when applying changes to managed software installations. I recommend that organizations with complex systems and heavy data requirements consider the capabilities of Palantir. Its platform encompasses end-to-end data processes and allows workers to deploy artificial intelligence and machine language for operational decision-making across various domains. With its decision modeling and situational intelligence capabilities, organizations can transform and automate traditional decision-making processes through an integrated infrastructure. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/AP_DM_Palantir%20Operationalizes%20Analytics%20and%20Data%20for%20Actions%20and%20Decisions.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": "Expanding the Analytics Continuum: From Analysis to Action", "mainEntityOfPage": "https://davidmenninger.isg-research.net/expanding-the-analytics-continuum-from-analysis-to-action", "datePublished": "02/08/2022", "dateModified": "02/08/2022", "articleBody": "I often use the term “analytics” to refer to a broad set of capabilities, deliberately broader than business intelligence. In this Perspective, I’d like to share what decision-makers should consider as they evaluate the range of analytics requirements for their organization. The analytics continuum comprises the many types of analyses organizations perform, including reporting, visualization, planning, real-time processes, natural language processing, artificial intelligence and machine learning. Our recent Analytics and Data Benchmark Research shows that reports and dashboards are still the most common type of analytics deployed today. This research also shows that, over time, organizations expect to be using AI/ML and natural language processing nearly as frequently as reports and dashboards. One of the most common benefits reported by participants in our research is that analytics improves communication and knowledge sharing within an organization. That said, today’s organizations must be able to do much more than just share knowledge, but also act on the information that is gathered and analyzed. Sometimes, acting on information is a matter of employing real-time analyses to respond in the moment, before an opportunity is lost. Both business-to-business and business-to-consumer customers have come to expect real-time responsiveness in their customer experiences. More than one-fifth (22%) of organizations are analyzing data in real time, and more than one-half (56%) are using or evaluating event streaming technologies. Analyzing data in real time, though, requires a different approach than analyzing historical data. As I’ve written previously, visualization may be useful in some situations, but it is not a very effective technique for real-time analyses that require automation to take the required action and generate a timely response. The automation required in many real-time scenarios depends on the use of AI/ML models to recommend the appropriate response based on information streaming into the organization. Our research shows that nearly 4 in 10 (38%) organizations are automating responses to event data. Many use cases can benefit from AI/ML analyses to determine the best action to take. Today’s powerful computing infrastructures allow for analysis of huge amounts of data using sophisticated algorithms, processing faster than ever before. These techniques help organizations predict behaviors or outcomes and use that information to automatically respond – for instance, with the best offer or recommendation given the current situation. Even when responses are not automated, AI/ML-assisted processes can help identify correlations that might not be discovered otherwise, such as finding a process that results in better customer segmentation for sales and marketing activities. AI/ML also drives the use of natural language processing, which makes analytics accessible to a wider audience within the organization. Beyond that, AI/ML enables the personalization that extends the analytics continuum, not just by type of analysis or type of data, but also by the role and habits of the individual. Across all of these different use cases, we assert that by 2025, 9 in ten analytics processes will be enhanced by artificial intelligence and machine learning to streamline operations and increase the value that can be derived from data. Still other actions might involve thorough evaluation of alternatives using driver-based planning capabilities in order to project and then compare the outcomes in different scenarios. While planning and predicting are both forward looking, they are not the same thing as I described in this Perspective. AI/ML gets more attention, but I believe that planning is just as important. Organizations can’t fully evaluate different actions without modeling the outcomes of those actions. My fear is that many organizations are still relying on spreadsheets for this part of the analytics process. In the end, the value of analytics is realized not from the analysis, but from the actions of the organization. To maximize value, the analytics continuum needs to connect back to business applications, to be connected to and orchestrated with operational applications in order to capture and implement the results of the analyses. I’m encouraged to see more analytics vendors beginning to address this need in their platforms. “Analytics” is a loaded term. It has many meanings and many components. Hopefully this explanation of the term will help you understand the breadth of analytics available in the market today and help you match those capabilities to the requirements of your organization. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/AP_DM_Expanding%20the%20Analytics%20Continuum_From%20Analysis%20to%20Action.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": "Zoho Unifies Data and Analytics", "mainEntityOfPage": "https://davidmenninger.isg-research.net/zoho-unifies-data-and-analytics", "datePublished": "07/07/2022", "dateModified": "07/07/2022", "articleBody": "Organizations are continuously increasing the use of analytics and business intelligence to turn data into meaningful and actionable insights. Our Analytics and Data Benchmark Research shows some of the benefits of using analytics: Improved efficiency in business processes, improved communication and gaining a competitive edge in the market top the list. With a unified BI system, organizations can have a comprehensive view of all organizational data to better manage processes and identify opportunities. Zoho is a software company that offers a suite of business applications across various segments. Zoho Analytics is its self-service BI platform that connects to various sources including on-premises and cloud databases, business applications, files and feed and custom apps. The platform enables individuals to cleanse, transform, enrich and catalog the data using its data preparation and management module. It also offers the capability to augment data analysis with artificial intelligence. Line-of-business workers can use its AI assistant to generate automated insights and perform cognitive and what-if analysis. The platform offers a drag and drop interface to create interactive reports and dashboards which can then be shared across the organization. Zoho recently announced the latest version of its low-code offering, Zoho Creator Platform. It enables line-of-business and IT teams to build scalable, low-code solutions that include apps, integrations, analytics and process automation without heavy dependency on IT teams or time-consuming training. With this update, Zoho’s Creator Platform combines application development, integrations, process automation, business intelligence and analytics into a single platform, enabling IT teams to manage security, compliance and governance challenges. In today’s ever-changing business landscape, it is important for organizations to use business intelligence and analytics effectively to outperform the competition. Our Analytics and Data Benchmark Research shows some of the most common complaints businesses have with existing analytics systems, including difficulty integrating with other business processes, not flexible enough when scaling, hard to access data sources and processes consuming too many resources. Zoho customers will find it straightforward to integrate Zoho Analytics with other Zoho products and blend data from various applications in the Zoho suite. Others will find the Zoho Analytics platform easy to use with a broad range of functionality and integrations. The platform can also be deployed on-premises and on third-party cloud infrastructures such as Google Cloud, Amazon Web Services and Microsoft Azure. Its data prep solution enables workers to connect, explore, transform and enrich data for analytics, machine learning, migration and data warehousing. The platform also connects to Zoho’s AI-powered analytical assistant, Zia, that analyzes and extracts insights in real time using machine learning to generate reports and dashboards from those insights. Zoho Workplace is its cloud office and productivity suite that enables real-time collaboration on different apps. Line-of-business workers can access all workplace applications through its centralized panel and connect with other team members using its business productivity tools to improve collaboration. Zoho One is a comprehensive suite of all of the company’s 45-plus business applications that further enhance the value an integrated offering provides. Connecting analytics with business applications and collaboration tools enables organizations to move from insight and collaborative decision-making to action. Ultimately, the objective of analyses is to take actions that improve an organization’s operations. Organizations attempting to combine data from multiple applications and run data processes, analytics and BI on a unified platform should evaluate the offerings of Zoho. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/AP_DM_Zoho%20Unifies%20Data%20and%20Analytics.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": "Denodo Advancing Data Virtualization in the Cloud", "mainEntityOfPage": "https://davidmenninger.isg-research.net/denodo-advancing-data-virtualization-in-the-cloud", "datePublished": "28/04/2022", "dateModified": "28/04/2022", "articleBody": "Organizations have been using data virtualization to collect and integrate data from various sources, and in different formats, to create a single source of truth without redundancy or overlap, thus improving and accelerating decision-making giving them a competitive advantage in the market. Our research shows that data virtualization is popular in the big data world. One-quarter (27%) of participants in our Data Lake Dynamic Insights Research reported they were currently using data virtualization, and another two-quarters (46%) planned to include data virtualization in the future. Even more interesting, those who are using data virtualization reported higher rates of satisfaction (79%) with their data lake than those who are not (36%). Our Analytics and Data Benchmark Research shows more than one-third of organizations (37%) are using data virtualization in that context. Here, too, those using data virtualization reported higher levels of satisfaction (88%) than those that are not (66%). Data virtualization makes it easier to incorporate a wide variety of data sources into a logical data lake. Data virtualization also helps organizations with data governance since data remains in the source platform, ensuring all access rights are maintained in a single system. Denodo is a data integration and virtualization company whose software connects to various data sources and can combine, aggregate, join and filter data to create reports in multiple formats, providing real-time access to integrated data across an organization. The Denodo Platform offers the capabilities of a logical data fabric including a data catalog, data governance, query acceleration powered by artificial intelligence (AI), cloud infrastructure management for multi-cloud and hybrid scenarios, and embedded data-preparation capabilities for self-service analytics. Denodo Platform 8.0 is its latest version and features support for additional types of users and use cases, such as data science and machine learning (ML) initiatives. It is now capable of automatically managing the cloud infrastructure from a centralized web console. And its engine can accelerate execution through an automatic query-rewriting process that identifies pre-calculated summaries that can be used to reduce execution time. Denodo Cloud is its set of services that can be deployed on cloud platforms including Amazon Web Services (AWS) Cloud, Microsoft Azure, Google Cloud Platform (GCP), private clouds, and hybrid cloud environments. It is now more important than ever for organizations with vast amounts of data spread across several repositories and lines of business to modernize their data architectures. IT teams face multiple challenges trying to keep up with new data sources as they are added. Deploying data virtualization technology can minimize the effort needed to access these new data sources. It also provides access to data and analytics in near real time. Each year, Ventana Research highlights the best use of digital technology with our Digital Leadership Award. This award recognizes the individual, organization and technology that support any or all of the following areas: analytics and data, artificial intelligence and machine learning, blockchain, cloud computing, collaborative and conversational computing, extended reality, internet of things, mobile computing and robotic automation. Last year, the 2021 Digital Leadership Award in Digital Technology went to Chad Simpson of City Furniture and his use of Denodo. With Denodo Platform’s data virtualization capabilities, City Furniture was able to eliminate the heavy software engineering efforts around processes to build data pipelines. Organizations must take action to ensure that operations in hybrid cloud computing environments have the technology to support data virtualization. Simplifying access and use of data in cloud computing requires an architectural approach that is not always top of mind. Consider that, according to our research, 86% of organizations expect most data will reside in the cloud, 99% expect to perform analytics in the cloud, and 33% have a primary data lake platform in the cloud. Organizations that are looking to more easily manage a diverse and growing set of data sources should consider Denodo’s offerings. Its platform offers access to a wider variety of cloud and on-premises data sources. It includes a unified, web-based interface that provides a data design studio, system management features, cloud deployment capabilities, and AI-powered query optimization. And, as our research shows, organizations using data virtualization enjoy higher rates of satisfaction than those that are not. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/AP_DM_Denodo%20Advancing%20Data%20Virtualization%20in%20the%20Cloud.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": "Don’t Rely on Dashboards for Real-Time Analytics", "mainEntityOfPage": "https://davidmenninger.isg-research.net/dont-rely-on-dashboards-for-real-time-analytics", "datePublished": "31/03/2022", "dateModified": "31/03/2022", "articleBody": "I have written previously that the world of data and analytics will become more and more centered around real-time, streaming data. Data is created constantly and increasingly is being collected simultaneously. Technology advances now enable organizations to process and analyze information as it is being collected to respond in real time to opportunities and threats. Not all use cases require real-time analysis and response, but many do, including multiple use cases that can improve customer experiences. For example, best-in-class e-commerce interactions should provide real-time updates on inventory status to avoid stock-out or back-order situations. Customer service interactions should provide real-time recommendations that minimize the time to resolution. Location-based offers should be targeted at the customer’s current location, not their location several minutes ago. Another domain where real-time analyses are critical is internet of things (IoT) applications. Additionally, use cases like predictive maintenance require timely information to prevent equipment failures that help avoid additional costs and damage. Our Analytics and Data Benchmark Research shows almost one-quarter (22%) of participants conduct real-time analyses of their data. Another 10% are analyzing data at least hourly. The research also shows a correlation between the frequency of analysis and an organization’s satisfaction with their analytics. Organizations performing real-time analyses report the highest levels of satisfaction. Those performing weekly or monthly analyses report the lowest levels of satisfaction. This correlation is not surprising. Individuals need timely analysis to inform their decision-making processes. We assert that by 2024, one-half of organizations will incorporate streaming analytics into their business processes, enabling them to respond to opportunities and threats faster. The research also explores whether organizations have adequate technologies to support different types of analyses. Half as many organizations (19%) report they have completely adequate technologies for real-time analysis compared with those that have completely adequate technologies for reports (38%) and dashboards (38%). Real-time analyses require a different approach. Having someone sit around and watch a dashboard waiting for information to change is not a very effective way to monitor changes. The data may be changing so frequently that it is hard to even see what is changing. Even if someone were to identify and understand the changes, would they be able to determine the correct response before it was too late? A proactive rather than reactive approach is needed. At a minimum, alerts and notifications can be used to draw attention to issues as they arise rather than expecting someone to watch a dashboard. Unfortunately, the technologies for alerts and notifications are not considered to be much better than the technologies for real-time analysis. It only solves one part of the problem — identifying an issue. Determining and implementing the correct response in real time is the other part of the challenge. In simple cases, evaluating and selecting the correct response can be done with heuristics or straightforward logic. However, it is more likely that artificial intelligence and machine learning (AI/ML) will be needed to effectively evaluate and select an appropriate response. Once an appropriate response is selected, it may need to be reviewed and approved (perhaps via an alert) and then implemented. The implementation may be a recommendation on a customer service screen, it may be updating the inventory status on an e-commerce screen, it may be placing a replenishment order, or it may be a combination of several actions. As organizations become more proactive and oriented around real-time processes, they need to adopt an event-driven approach to their operations. Nearly one-half (48%) are using streaming data in their operational processes, yet only 15% report their event-streaming technologies are completely adequate. Real-time and streaming require a focus on event-driven architectures to support responsiveness and are on the path to what we call a digital business. Analytics vendors must recognize the needs organizations have for real-time operations. They will not be solved by reports and dashboards. Organizations need better alert and notification capabilities. They also require improved AI/ML capabilities to evaluate the appropriate actions to take. And they need enhanced agent technologies to connect the various applications — analytical and operational — involved in taking action. In the meantime, organizations should consider third-party technologies for some of these capabilities. We continue to study the issues associated with real-time analyses and event-driven architectures in our Streaming Data Dynamic Insights Research. Please contribute to this research with input from your organization. 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