ISG Software Research Analyst Perspectives

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We offer a portfolio of advisory, research, thought leadership and digital education services to help optimize market strategy, planning and execution. <a href="https://www.ventanaresearch.com/services/vendors/analyst_relations" rel="noopener">Analyst Relations</a> <a href="https://www.ventanaresearch.com/services/vendors/demand_generation" rel="noopener">Demand Generation</a> <a href="https://www.ventanaresearch.com/services/vendors/product-marketing" rel="noopener">Product Marketing</a> <a href="https://www.ventanaresearch.com/vendor-coverage" target="_self" role="menuitem">Market Coverage</a> <a href="https://www.ventanaresearch.com/briefing" target="_self" role="menuitem">Request a Briefing</a> </div> <ul></ul> <div class="bottom_rich_text"> </div> </div> </div> </div> </div> </div> <script src="https://blog.isg-research.net/hs-fs/hub/2035844/hub_generated/template_assets/90531223305/1725882478811/Ventana_Research_2023/js/mmenu.min.js"></script> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div id="hs_cos_wrapper_Structured_data" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"></div> <div class="body-container-wrapper"> <div class="blog-header background-image post_page_2" data-bg-color="secondary" style="background-size:cover;background-position:50%;background-repeat:no-repeat;background-image:url(https://blog.isg-research.net/hubfs/_images/_backgrounds/314838419_1200px.jpg)">  <div class="row-fluid"> <div class="blog-header__inner dnd-row"> <div class="blog--post__image dnd-section">  <h1 class="analyst-header-title">Analyst Perspectives</h1>  </div> </div> </div> </div> <div class="content-wrapper-listing blog-single"> <div class="blog-content-wrapper"> <div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2016/11/09/splunk-delivers-insights-from-machines/">Splunk Delivers Insights from Machines</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/david-menninger"> David Menninger </a> on 09 November 2016 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="//blog.isg-research.net/hs-fs/hubfs/Ventana_Research_Sept_2016/images/shutterstock_314838419-1.jpg?width=200&name=shutterstock_314838419-1.jpg" width="200" !important: srcset="//blog.isg-research.net/hs-fs/hubfs/Ventana_Research_Sept_2016/images/shutterstock_314838419-1.jpg?width=100&name=shutterstock_314838419-1.jpg 100w, //blog.isg-research.net/hs-fs/hubfs/Ventana_Research_Sept_2016/images/shutterstock_314838419-1.jpg?width=200&name=shutterstock_314838419-1.jpg 200w, //blog.isg-research.net/hs-fs/hubfs/Ventana_Research_Sept_2016/images/shutterstock_314838419-1.jpg?width=300&name=shutterstock_314838419-1.jpg 300w, //blog.isg-research.net/hs-fs/hubfs/Ventana_Research_Sept_2016/images/shutterstock_314838419-1.jpg?width=400&name=shutterstock_314838419-1.jpg 400w, //blog.isg-research.net/hs-fs/hubfs/Ventana_Research_Sept_2016/images/shutterstock_314838419-1.jpg?width=500&name=shutterstock_314838419-1.jpg 500w, //blog.isg-research.net/hs-fs/hubfs/Ventana_Research_Sept_2016/images/shutterstock_314838419-1.jpg?width=600&name=shutterstock_314838419-1.jpg 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> I recently attended .conf2016, Splunk’s seventh annual user conference. Splunk created the market for analyzing machine data (shorthand for machine-generated data), which consists of log files and event data from various types of systems and devices. Our <a href="//www.ventanaresearch.com/BigDataAnalytics/" target="_blank">big data analytics benchmark research</a> shows that these are two of the most common sources of big data that organizations analyze. This market has proven to be fertile ground for Splunk, growing steadily with revenues more than doubling over the... </div> <a href="https://blog.isg-research.net/2016/11/09/splunk-delivers-insights-from-machines/"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/machine-learning">Machine Learning</a>, <a href="https://blog.isg-research.net/topic/splunk">Splunk</a>, <a href="https://blog.isg-research.net/topic/analytics">Analytics</a>, <a href="https://blog.isg-research.net/topic/machine-data">Machine data</a>, <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence</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://blog.isg-research.net/2015/02/08/big-data-research-agenda-and-trends-are-bolder-in-2015">Big Data Research Agenda and Trends are Bolder in 2015</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/mark-smith"> Mark Smith </a> on 07 February 2015 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/ventanaresearchlogo300px2-1.png?width=200&name=ventanaresearchlogo300px2-1.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/ventanaresearchlogo300px2-1.png?width=100&name=ventanaresearchlogo300px2-1.png 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/ventanaresearchlogo300px2-1.png?width=200&name=ventanaresearchlogo300px2-1.png 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/ventanaresearchlogo300px2-1.png?width=300&name=ventanaresearchlogo300px2-1.png 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/ventanaresearchlogo300px2-1.png?width=400&name=ventanaresearchlogo300px2-1.png 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/ventanaresearchlogo300px2-1.png?width=500&name=ventanaresearchlogo300px2-1.png 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/ventanaresearchlogo300px2-1.png?width=600&name=ventanaresearchlogo300px2-1.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> Big data has become a big deal as the technology industry has invested tens of billions of dollars to create the next generation of databases and data processing. After the accompanying flood of new categories and marketing terminology from vendors, most in the IT community are now beginning to understand the potential of big data. Ventana Research thoroughly covered the evolving state of the big data and information optimization sector in 2014 and will continue this research in 2015 and... </div> <a href="https://blog.isg-research.net/2015/02/08/big-data-research-agenda-and-trends-are-bolder-in-2015"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/big-data">Big Data</a>, <a href="https://blog.isg-research.net/topic/mapr">MapR</a>, <a href="https://blog.isg-research.net/topic/predictive-analytics">Predictive Analytics</a>, <a href="https://blog.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://blog.isg-research.net/topic/sap">SAP</a>, <a href="https://blog.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://blog.isg-research.net/topic/human-capital">Human Capital</a>, <a href="https://blog.isg-research.net/topic/marketing">Marketing</a>, <a href="https://blog.isg-research.net/topic/mulesoft">Mulesoft</a>, <a href="https://blog.isg-research.net/topic/paxata">Paxata</a>, <a href="https://blog.isg-research.net/topic/snaplogic">SnapLogic</a>, <a href="https://blog.isg-research.net/topic/splunk">Splunk</a>, <a href="https://blog.isg-research.net/topic/customer-performance">Customer Performance</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/cloudera">Cloudera</a>, <a href="https://blog.isg-research.net/topic/financial-performance">Financial Performance</a>, <a href="https://blog.isg-research.net/topic/hortonworks">Hortonworks</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/informatica">Informatica</a>, <a href="https://blog.isg-research.net/topic/information-management">Information Management</a>, <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://blog.isg-research.net/topic/oracle">Oracle</a>, <a href="https://blog.isg-research.net/topic/datawatch">Datawatch</a>, <a href="https://blog.isg-research.net/topic/dell-boomi">Dell Boomi</a>, <a href="https://blog.isg-research.net/topic/information-optimization">Information Optimization</a>, <a href="https://blog.isg-research.net/topic/savi">Savi</a>, <a href="https://blog.isg-research.net/topic/sumo-logic">Sumo Logic</a>, <a href="https://blog.isg-research.net/topic/tamr">Tamr</a>, <a href="https://blog.isg-research.net/topic/trifacta">Trifacta</a>, <a href="https://blog.isg-research.net/topic/stratahadoop">Strata+Hadoop</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2013/08/13/three-major-trends-in-new-discovery-analytics">Three Major Trends in New Discovery Analytics</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/isg-software-research"> ISG Software Research </a> on 13 August 2013 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_predanalytics_predictive_analytics_obstacles-9.png?width=200&name=vr_predanalytics_predictive_analytics_obstacles-9.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_predanalytics_predictive_analytics_obstacles-9.png?width=100&name=vr_predanalytics_predictive_analytics_obstacles-9.png 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_predanalytics_predictive_analytics_obstacles-9.png?width=200&name=vr_predanalytics_predictive_analytics_obstacles-9.png 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_predanalytics_predictive_analytics_obstacles-9.png?width=300&name=vr_predanalytics_predictive_analytics_obstacles-9.png 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_predanalytics_predictive_analytics_obstacles-9.png?width=400&name=vr_predanalytics_predictive_analytics_obstacles-9.png 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_predanalytics_predictive_analytics_obstacles-9.png?width=500&name=vr_predanalytics_predictive_analytics_obstacles-9.png 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_predanalytics_predictive_analytics_obstacles-9.png?width=600&name=vr_predanalytics_predictive_analytics_obstacles-9.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> A few months ago, I wrote an article on the <a href="http://tonycosentino.ventanaresearch.com/2013/03/11/the-four-pillars-of-big-data-analytics/" target="_blank">four pillars of big data analytics</a>. One of those pillars is what is called discovery analytics or where visual analytics and data discovery combine together to meet the business and analyst needs. My colleague <a href="//marksmith.ventanaresearch.com/2013/05/07/four-types-of-discovery-technology-for-using-big-data-intelligently/" target="_blank">Mark Smith subsequently clarified</a> the four types of discovery analytics: visual discovery, data discovery, information discovery and event discovery. Now I want to follow up with a discussion of three trends that our research has uncovered in... </div> <a href="https://blog.isg-research.net/2013/08/13/three-major-trends-in-new-discovery-analytics"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/datameer">Datameer</a>, <a href="https://blog.isg-research.net/topic/sap">SAP</a>, <a href="https://blog.isg-research.net/topic/splunk">Splunk</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/analytics">Analytics</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://blog.isg-research.net/topic/information-builders">Information Builders</a>, <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://blog.isg-research.net/topic/oracle">Oracle</a>, <a href="https://blog.isg-research.net/topic/data-discovery">Data Discovery</a>, <a href="https://blog.isg-research.net/topic/information-discovery">Information Discovery</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://blog.isg-research.net/2013/02/09/splunk-provides-operational-intelligence-in-the-cloud">Splunk Provides Operational Intelligence in the Cloud</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/mark-smith"> Mark Smith </a> on 09 February 2013 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo1-4.jpg?width=200&name=vr_2012_techaward_winner_logo1-4.jpg" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo1-4.jpg?width=100&name=vr_2012_techaward_winner_logo1-4.jpg 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo1-4.jpg?width=200&name=vr_2012_techaward_winner_logo1-4.jpg 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo1-4.jpg?width=300&name=vr_2012_techaward_winner_logo1-4.jpg 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo1-4.jpg?width=400&name=vr_2012_techaward_winner_logo1-4.jpg 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo1-4.jpg?width=500&name=vr_2012_techaward_winner_logo1-4.jpg 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo1-4.jpg?width=600&name=vr_2012_techaward_winner_logo1-4.jpg 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> Splunk’s innovated ability to access and use machine data for targeted operational insights can help improve IT and enhance business operational efficiency. Its work to capitalize on big data was part of <a href="//marksmith.ventanaresearch.com/2012/04/27/splunk-big-data-machine-for-operational-intelligence/" target="_blank">my last analysis</a>, while my colleague Tony Cosentino looked at its focus on <a href="http://tonycosentino.ventanaresearch.com/2012/09/14/splunk-bids-to-be-king-of-search-and-operational-analytics/" target="_blank">search and operational analytics</a>. Splunk also was a recipient of the <a href="//www.ventanaresearch.com/resources/resources.aspx?id=3519" target="_blank">2012 Ventana Research Technology Innovation Award for IT Performance</a> for <a href="http://www.splunk.com/view/splunk/SP-CAAAG57" target="_blank">Splunk Enterprise</a>. </div> <a href="https://blog.isg-research.net/2013/02/09/splunk-provides-operational-intelligence-in-the-cloud"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/big-data">Big Data</a>, <a href="https://blog.isg-research.net/topic/splunk">Splunk</a>, <a href="https://blog.isg-research.net/topic/it-performance">IT Performance</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://blog.isg-research.net/topic/information-management">Information Management</a>, <a href="https://blog.isg-research.net/topic/machine-data">Machine data</a>, <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence</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://blog.isg-research.net/2012/11/18/a-decade-of-research-at-ventana-research">A Decade of Research at Ventana Research</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/mark-smith"> Mark Smith </a> on 18 November 2012 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_bti_br_whats_driving_change_to_technology_selection-12.png?width=200&name=vr_bti_br_whats_driving_change_to_technology_selection-12.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_bti_br_whats_driving_change_to_technology_selection-12.png?width=100&name=vr_bti_br_whats_driving_change_to_technology_selection-12.png 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_bti_br_whats_driving_change_to_technology_selection-12.png?width=200&name=vr_bti_br_whats_driving_change_to_technology_selection-12.png 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_bti_br_whats_driving_change_to_technology_selection-12.png?width=300&name=vr_bti_br_whats_driving_change_to_technology_selection-12.png 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_bti_br_whats_driving_change_to_technology_selection-12.png?width=400&name=vr_bti_br_whats_driving_change_to_technology_selection-12.png 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_bti_br_whats_driving_change_to_technology_selection-12.png?width=500&name=vr_bti_br_whats_driving_change_to_technology_selection-12.png 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_bti_br_whats_driving_change_to_technology_selection-12.png?width=600&name=vr_bti_br_whats_driving_change_to_technology_selection-12.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> I’m happy to say that Ventana Research celebrated its tenth anniversary at our recent <a href="//www.ventanaresearch.com/resources/resources.aspx?id=3499" target="_blank">Business Technology Innovation Summit</a> in San Jose at the Tech Museum. This location was fitting, since at the event we introduced and presented our first-ever <a href="//www.ventanaresearch.com/resources/resources.aspx?id=3453" target="_blank">Technology Innovation Awards</a> and seventh annual <a href="//www.ventanaresearch.com/resources/resources.aspx?id=3443" target="_blank">Leadership Awards</a>. If you did not get a chance to attend, we have the live webstream <a href="http://fora.tv/conference/ventana_research_business_technology_innovation_summit_2012" target="_blank">available for replay</a> at no cost; thanks to Splunk for sponsoring this to let everyone enjoy the sessions. </div> <a href="https://blog.isg-research.net/2012/11/18/a-decade-of-research-at-ventana-research"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://blog.isg-research.net/topic/sap">SAP</a>, <a href="https://blog.isg-research.net/topic/social-media">Social Media</a>, <a href="https://blog.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://blog.isg-research.net/topic/peoplefluent">Peoplefluent</a>, <a href="https://blog.isg-research.net/topic/planview">Planview</a>, <a href="https://blog.isg-research.net/topic/research">Research</a>, <a href="https://blog.isg-research.net/topic/splunk">Splunk</a>, <a href="https://blog.isg-research.net/topic/it-performance">IT Performance</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/cio">CIO</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/financial-performance">Financial Performance</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://blog.isg-research.net/topic/information-management">Information Management</a>, <a href="https://blog.isg-research.net/topic/location-intelligence">Location Intelligence</a>, <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://blog.isg-research.net/topic/workforce-performance">Workforce Performance</a>, <a href="https://blog.isg-research.net/topic/ceridian">Ceridian</a>, <a href="https://blog.isg-research.net/topic/cfo">CFO</a>, <a href="https://blog.isg-research.net/topic/cmo">CMO</a>, <a href="https://blog.isg-research.net/topic/coo">COO</a>, <a href="https://blog.isg-research.net/topic/datawatch">Datawatch</a>, <a href="https://blog.isg-research.net/topic/saba">Saba</a>, <a href="https://blog.isg-research.net/topic/technology">Technology</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://blog.isg-research.net/2012/09/14/splunk-bids-to-be-king-of-search-and-operational-analytics">Splunk Bids to be King of Search and Operational Analytics</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/isg-software-research"> ISG Software Research </a> on 14 September 2012 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_infomgt_barriers_to_information_management-14.png?width=200&name=vr_infomgt_barriers_to_information_management-14.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_infomgt_barriers_to_information_management-14.png?width=100&name=vr_infomgt_barriers_to_information_management-14.png 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_infomgt_barriers_to_information_management-14.png?width=200&name=vr_infomgt_barriers_to_information_management-14.png 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_infomgt_barriers_to_information_management-14.png?width=300&name=vr_infomgt_barriers_to_information_management-14.png 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_infomgt_barriers_to_information_management-14.png?width=400&name=vr_infomgt_barriers_to_information_management-14.png 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_infomgt_barriers_to_information_management-14.png?width=500&name=vr_infomgt_barriers_to_information_management-14.png 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_infomgt_barriers_to_information_management-14.png?width=600&name=vr_infomgt_barriers_to_information_management-14.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> As I listened to the keynote address at, <a href="http://www.splunk.com/goto/conf" target="_blank">conf2012</a>, the annual Splunk user conference, my initial impression was that the company was spreading itself too thin. The company highlighted four rather formidable areas of organizational focus: Enterprise 5.0, the company’s flagship data platform, which is now in beta; Development, which is support for building applications and integrating Splunk within the broader IT infrastructure; Content, the continued development of core applications and use... </div> <a href="https://blog.isg-research.net/2012/09/14/splunk-bids-to-be-king-of-search-and-operational-analytics"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/big-data">Big Data</a>, <a href="https://blog.isg-research.net/topic/splunk">Splunk</a>, <a href="https://blog.isg-research.net/topic/data-fabric">data fabric</a>, <a href="https://blog.isg-research.net/topic/it-performance">IT Performance</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/analytics">Analytics</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://blog.isg-research.net/topic/digital-technology">Digital Technology</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://blog.isg-research.net/2012/05/22/splunk-provides-intelligence-for-customer-analytics">Splunk Provides Intelligence for Customer Analytics</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/isg-software-research"> ISG Software Research </a> on 22 May 2012 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="" width="200" !important:> </div> Recently my colleague Mark Smith wrote about Splunk and its latest technology supporting analytics for IT on machine data and providing <a href="//marksmith.ventanaresearch.com/2012/04/27/splunk-big-data-machine-for-operational-intelligence/">operational intelligence</a>. I wasn’t familiar with the company, which has focused on IT users and improving the performance of a company’s networks and IT systems. From a customer management perspective, these are of little interest unless they impact the customer experience; for example, if the website is down or the online banking system is unavailable. But in... </div> <a href="https://blog.isg-research.net/2012/05/22/splunk-provides-intelligence-for-customer-analytics"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://blog.isg-research.net/topic/customer-experience">Customer Experience</a>, <a href="https://blog.isg-research.net/topic/social-crm">Social CRM</a>, <a href="https://blog.isg-research.net/topic/splunk">Splunk</a>, <a href="https://blog.isg-research.net/topic/it-performance">IT Performance</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-mobility">Business Mobility</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/customer-service">Customer Service</a>, <a href="https://blog.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://blog.isg-research.net/topic/information-management">Information Management</a>, <a href="https://blog.isg-research.net/topic/workforce-performance">Workforce Performance</a>, <a href="https://blog.isg-research.net/topic/call-center">Call Center</a>, <a href="https://blog.isg-research.net/topic/contact-center">Contact Center</a>, <a href="https://blog.isg-research.net/topic/crm">CRM</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://blog.isg-research.net/2012/04/27/splunk-big-data-machine-for-operational-intelligence">Splunk: Big Data Machine for Operational Intelligence</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/mark-smith"> Mark Smith </a> on 27 April 2012 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="" width="200" !important:> </div> <a href="http://www.splunk.com" target="_blank">Splunk</a> recently entered the financial markets as a publicly traded company (NASDAQ: SPLK) and also entered a new phase in its corporate growth. Splunk combines the power of search and discovery with analytics on data generated by IT systems, that they call machine data, and provide insight for a new generation of operational intelligence that helps everyone in IT including the CIO determine the efficiency of its systems that support business. The company has built a platform that can index data... </div> <a href="https://blog.isg-research.net/2012/04/27/splunk-big-data-machine-for-operational-intelligence"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/big-data">Big Data</a>, <a href="https://blog.isg-research.net/topic/social-media">Social Media</a>, <a href="https://blog.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://blog.isg-research.net/topic/splunk">Splunk</a>, <a href="https://blog.isg-research.net/topic/it-performance">IT Performance</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-mobility">Business Mobility</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/business-technology">Business Technology</a>, <a href="https://blog.isg-research.net/topic/cio">CIO</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/financial-performance">Financial Performance</a>, <a href="https://blog.isg-research.net/topic/governance-risk-compliance-grc">Governance, Risk & Compliance (GRC)</a>, <a href="https://blog.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://blog.isg-research.net/topic/information-management">Information Management</a>, <a href="https://blog.isg-research.net/topic/information-technology">Information Technology</a>, <a href="https://blog.isg-research.net/topic/it-analytics">IT Analytics</a>, <a href="https://blog.isg-research.net/topic/location-intelligence">Location Intelligence</a>, <a href="https://blog.isg-research.net/topic/machine-data">Machine data</a>, <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://blog.isg-research.net/topic/stratahadoop">Strata+Hadoop</a> <hr> </div> <script> // Check active classes var checkClass = function() { if ( $('.fil_item').hasClass('hide') ) { $('.fil_item').removeClass('hide'); 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srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=50&name=Menninger.David%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=150&name=Menninger.David%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=200&name=Menninger.David%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=250&name=Menninger.David%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=300&name=Menninger.David%20Pic.Circle.png 300w"> <h5 class="analyst_name">David Menninger</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://jefforr.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png" alt="Jeff Orr" width="100" data-constrained="true" caption="false" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=50&name=Orr.Jeff.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=150&name=Orr.Jeff.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=200&name=Orr.Jeff.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=250&name=Orr.Jeff.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=300&name=Orr.Jeff.Circle.png 300w" sizes="(max-width: 100px) 100vw, 100px"> <h5 class="analyst_name">Jeff Orr</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://keithdawson.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png" alt="Keith Dawson" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=50&name=Dawson.Keith%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=150&name=Dawson.Keith%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=200&name=Dawson.Keith%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=250&name=Dawson.Keith%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=300&name=Dawson.Keith%20Pic.Circle.png 300w"> <h5 class="analyst_name">Keith Dawson</h5> </a> </div> <div class="span6" style="text-align:center;"> <a href="https://marksmith.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png" alt="Mark Smith" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=50&name=Smith.Mark%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=150&name=Smith.Mark%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=200&name=Smith.Mark%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=250&name=Smith.Mark%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=300&name=Smith.Mark%20Pic.Circle.png 300w"> <h5 class="analyst_name">Mark Smith</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://mattaslett.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png" alt="Matt Aslett" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=50&name=Aslett.Matt%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=150&name=Aslett.Matt%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=200&name=Aslett.Matt%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=250&name=Aslett.Matt%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=300&name=Aslett.Matt%20Pic.Circle.png 300w"> <h5 class="analyst_name">Matt Aslett</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://matthewbrown.isg-research.net/"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png" alt="Matthew Brown" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=50&name=profile_vr_matthew_brown_circle_900x900.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=150&name=profile_vr_matthew_brown_circle_900x900.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=200&name=profile_vr_matthew_brown_circle_900x900.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=250&name=profile_vr_matthew_brown_circle_900x900.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=300&name=profile_vr_matthew_brown_circle_900x900.png 300w"> <h5 class="analyst_name">Matthew Brown</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://robertkugel.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png" alt="Robert Kugel" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=50&name=Kugel.Robert%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=150&name=Kugel.Robert%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=200&name=Kugel.Robert%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=250&name=Kugel.Robert%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=300&name=Kugel.Robert%20Pic.Circle.png 300w"> <h5 class="analyst_name">Robert Kugel</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://stephenhurrell.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png" alt="Stephen Hurrell" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=50&name=Hurrell.Stephen%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png 100w, 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href="https://blog.isg-research.net/archive/2010/06">June 2010 (1)</a> </li> </ul> <a class="filter-expand-link" href="#">see all</a> </div> </div> <div class="block"> <h3>Posts by Topic</h3> <div class="widget-module"> <ul> <li> <a href="https://blog.isg-research.net/topic/10q">10Q (1)</a> </li> <li> <a href="https://blog.isg-research.net/topic/vendor-references">[Vendor references] (2)</a> </li> <li> <a href="https://blog.isg-research.net/topic/absolute-data">Absolute Data (1)</a> </li> <li> <a href="https://blog.isg-research.net/topic/accessibility">Accessibility (1)</a> </li> <li> <a href="https://blog.isg-research.net/topic/accountants">accountants (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/accounting">Accounting (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/accounting-close">accounting close (2)</a> </li> <li style="display:none;"> <a 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href="https://blog.isg-research.net/topic/closed-loop">closed loop (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/closing">closing (35)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cloud">Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cloud-analytics">cloud analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cloud-business-intelligence">cloud business intelligence (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing (863)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cloud-erp">cloud ERP (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cloud9-analytics">Cloud9 Analytics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cloudera">Cloudera (17)</a> </li> 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<a href="https://blog.isg-research.net/topic/corvisa-cloud">Corvisa Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cost-management">Cost Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/costing">costing (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cpaas">CPaaS (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cpq">CPQ (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/credit">credit (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/crisis">crisis (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/crm">CRM (267)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/crm-customer-service">CRM customer service (1)</a> </li> <li style="display:none;"> <a 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style="display:none;"> <a href="https://blog.isg-research.net/topic/deep-learning">Deep Learning (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dell">Dell (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dell-boomi">Dell Boomi (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/demand-chain">Demand Chain (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/demand-generation">Demand Generation (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/demand-management">demand management (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/demand-planning">Demand Planning (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/design">design (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/designed-data">designed data (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/desktop-analytics">Desktop Analytics (124)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/development">development (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/devops-and-platforms">DevOps and Platforms (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/devsecops">DevSecOps (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/df11">DF11 (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dg">DG (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dhcp">DHCP (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-applications">Digital Applications (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-business">Digital Business (47)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-commerce">Digital Commerce (104)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-communications">Digital Communications (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-experience-platform">Digital Experience Platform (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-finance">digital finance (106)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-innovation-awards">Digital Innovation Awards (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-intelligence">Digital Intelligence (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-interviewing">Digital Interviewing (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-marketing">Digital Marketing (28)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-operations">Digital Operations (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-publishing">Digital Publishing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-security">Digital Security (23)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-technology">Digital Technology (292)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-transformation">Digital transformation (20)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/direct-data-mapping">Direct Data Mapping (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/disaster-recovery">Disaster Recovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/discovery">Discovery (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/discovery-analytics">discovery analytics (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/discovery-tools">discovery tools (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/distribution">distribution (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dns">DNS (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/document-management">Document Management (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dodd-frank">Dodd-Frank (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/domestic-payroll">Domestic Payroll (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/domo">Domo (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dovetail">Dovetail (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dreamforce">Dreamforce (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/driver-analysis">driver analysis (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/driver-based">driver-based (14)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/driver-based-planning">driver-based planning (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dynamics">Dynamics (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dynamics-ax">Dynamics AX (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dynamics-gp">Dynamics GP (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dynamics-nav-dynamics-sl">Dynamics NAV Dynamics SL (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/e-discovery">e-discovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/echopass">Echopass (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/eclipse">Eclipse (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/edi">EDI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ediscovery">eDiscovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/editorial">Editorial (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/effectiveness">effectiveness (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/eg-solutions">eg Solutions (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/elasticube">elasticube (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/eloqua">Eloqua (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/embedded-analytics">embedded analytics (95)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/emc">EMC (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/employee-engagement">Employee Engagement (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/employee-experience">employee experience (47)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/employee-onboarding">Employee Onboarding (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/employee-productivity">Employee Productivity (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/empower">Empower (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/end-to-end">end-to-end (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/endeca">endeca (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enghouse-interactive">Enghouse interactive (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enkata">Enkata (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-applications">Enterprise Applications (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-data-strategy">Enterprise Data Strategy (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-messaging-internet-of-things-iot-middle">Enterprise messaging, Internet of Things, IoT, mid (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-profitability-management">enterprise profitability management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-resource-planning">Enterprise Resource Planning (72)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-risk-management">enterprise risk management (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-software">Enterprise Software (27)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-spreadsheet">enterprise spreadsheet (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-tax">Enterprise Tax (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterworks">Enterworks (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/environment-management">Environment Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/environmental">Environmental (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/envision">Envision (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/epicor">Epicor (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/epiphany">Epiphany (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/equifax">Equifax (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/equity-research">equity research (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/erm">ERM (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/erp">ERP (83)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/erp-and-continuous-accounting">ERP and Continuous Accounting (151)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/error">error (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/esg">ESG (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/esri">ESRI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/essbase">Essbase (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ethority">eThority (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-data">Event Data (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-discovery">Event discovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-stream">Event Stream (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-stream-processing">Event Stream Processing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-streams">Event Streams (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exacttarget">ExactTarget (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exadata">exadata (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exalytics">Exalytics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/excel">Excel (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/excentive">Excentive (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/executive">executive (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/expense">expense (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/expense-management">expense management (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/experience-management">Experience Management (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/expert-systems">Expert Systems (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exploration">Exploration (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exploratory-analytics">exploratory analytics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/explorium">Explorium (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/extended-close">extended close (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/extended-reality">extended reality (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/external-data-platform">External Data Platform (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exterro">Exterro (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/f-type">F-Type (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fasb">FASB (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fast-close">Fast close (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/feedback">Feedback (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fei">FEI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ferf-ceo">FERF CEO (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/field-service">Field Service (29)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance">finance (53)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-analytics">Finance Analytics (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-cloud">finance cloud (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-financial-applications-financial-close">Finance Financial Applications Financial Close (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-performance-management">Finance Performance Management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-transformation">finance transformation (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial">financial (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-analytics">financial analytics (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-applications">Financial Applications (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-close">Financial Close (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-governance">Financial Governance (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-management">Financial Management (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-model">financial model (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-performance">Financial Performance (561)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-performance-2">financial performance (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-performance-management">Financial Performance Management (237)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-performance-management-fpm">Financial Performance Management (FPM) (14)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-planning">financial planning (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-regulation">financial regulation (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-reporting">financial reporting (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-risk-management">financial risk management (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-services">Financial Services (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-software">financial software (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-standards">financial standards (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-statement">financial statement (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-systems">financial systems (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financialforce">FinancialForce (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financialforce-com">FinancialForce.com (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financials">financials (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/five9">Five9 (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/flow">flow (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fms">FMS (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/for-example-genesys">for example Genesys (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/forecast">Forecast (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/forecasting">forecasting (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fpa">FP&A (22)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fpm">FPM (83)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fraud">Fraud (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fuel50">Fuel50 (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fusion-applications">Fusion Applications (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/gaap">GAAP (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/gamifiacation">Gamifiacation (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/gartner">Gartner (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/genai">GenAI (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/generative-ai">Generative AI (38)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/genesys">Genesys (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/geographic-information-systems">Geographic Information Systems (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/gis">GIS (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/global-payroll">Global Payroll (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/globoforce">Globoforce (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/golden-records">Golden Records. (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/gooddata">Gooddata (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/google">Google (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/governance">Governance (49)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/governance-risk">Governance & Risk (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/governance-risk-and-compliance">Governance Risk and Compliance (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/governance-risk-compliance-grc">Governance, Risk & Compliance (GRC) (143)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/grc">GRC (55)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/grc-governance-risk-compliance-risk-management-wat">GRC, governance, risk, compliance, risk management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/green">Green (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/greenplum">Greenplum (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/gui">GUI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/hadoop">Hadoop (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/hana">HANA (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/harvard-business-review">Harvard Business Review (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/hawq">HAWQ (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/hcm">HCM (57)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/hcm-analytics">HCM Analytics (1)</a> </li> <li 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href="https://blog.isg-research.net/topic/jobscience">Jobscience (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/jobvite">JobVite (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/johnson-controls-panoptix">Johnson Controls Panoptix (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/jonova">Jonova (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/journalism">Journalism (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/json">JSON (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/kalido">Kalido (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/kana">Kana (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/kapow">Kapow (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/kapplets">Kapplets (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/karmasphere">Karmasphere (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/kenandy">Kenandy (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/kenexa">Kenexa (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/key-performance-indicators">Key Performance Indicators (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/key-performance-indictors">Key Performance Indictors (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/kinaxis">Kinaxis (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/knoahsoft">KnoahSoft (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/knopahsoft">KnopahSoft (1)</a> </li> <li 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(1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pentaho">Pentaho (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/people-analytics">People Analytics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/people-cloud">People Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/peoplefluent">Peoplefluent (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/peoplesoft">PeopleSoft (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/performance">Performance (30)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/performance-analytics">Performance Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/performance-management">Performance Management (89)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/perillon">Perillon (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/personalization">Personalization (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pervasive">Pervasive (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pim">PIM (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pim-product-information-management-sales-marketing">PIM, Product Information Management, Sales, Market (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pipkins">Pipkins (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pitney-bowes">Pitney Bowes (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pivotal-hd">Pivotal HD (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pivotlink">PivotLink (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/planmill">PlanMill (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/planning">Planning (88)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/planview">Planview (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/plateau">Plateau (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/platfora">Platfora (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/platform-as-a-service">Platform as a service (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/playbook">Playbook (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/plex">Plex (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/plunk">Plunk (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/portfolio-management">Portfolio Management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/portrait-software">Portrait Software (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/potus-department-of-labor-flsa-part-541-overtime-r">POTUS, Department of Labor, FLSA, Part 541, Overti (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/powercenter">PowerCenter (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predictive">Predictive (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predictive-analytics">Predictive Analytics (203)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predictive-hcm">Predictive HCM (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predictive-planning">Predictive Planning (49)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predixion">Predixion (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/price-and-revenue-management">Price and Revenue Management (70)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/price-optimization">Price Optimization (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pricing-and-promotion-management">Pricing and Promotion Management (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pricing-management">pricing management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pro">PRO (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/process-management">process management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/process-mining">Process Mining (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/procure-to-pay">Procure-to-Pay (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/procurement">procurement (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/product-experience-management">product experience management (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/product-information-management">Product Information Management (90)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/professional-services">Professional Services (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/professional-services-automation">Professional Services Automation (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/profit-velocity">Profit Velocity (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/profitability">Profitability (14)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/profitability-management">profitability management (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/project-management">Project Management (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/project-planning">Project Planning (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/project-portfolio-management">Project Portfolio Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/projecthelp">ProjectHelp (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/projectops">ProjectOps (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/projector">Projector (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/promptbook">Promptbook (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/property-technology">Property Technology (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pros">PROS (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pros-pricing">PROS Pricing (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/psa">PSA (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/publishing">Publishing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/purchasing">purchasing (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/purchasing-sourcing-payments">Purchasing/Sourcing/Payments (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pv-accelerator">PV Accelerator (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pxm">PXM (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qad">QAD (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlik">Qlik (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlik-qlik-sense">Qlik Qlik Sense (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlik-qonnections">Qlik Qonnections (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlik-analytics-qlik-sense-qlik-business-intelligen">Qlik, Analytics, Qlik Sense, Qlik, Business intell (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qliktech">Qliktech (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlikview">QlikView (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qualtrics">Qualtrics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/quantrix">Quantrix (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/quinterian">Quinterian (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/quotas">Quotas (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qvidian">Qvidian (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/r">R (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ransomware">Ransomware (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rapide">Rapide (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rapidminer">Rapidminer (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rdbms">RDBMS (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/real-estate">real estate (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/real-time">Real-time (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/reconciliation">Reconciliation (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/recovery">Recovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/recruiting">Recruiting (41)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/recurring-revenue">Recurring Revenue (19)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/report">report (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/reporting">Reporting (78)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/reporting-xbrl-ixbrl-document-management">Reporting, XBRL, iXBRL, document management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/research">Research (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/resilience">Resilience (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/responsetek">ResponseTek (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/retail-analytics">Retail Analytics (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue">Revenue (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-and-lease-accounting">revenue and lease accounting (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-management">Revenue Management (33)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-performance">Revenue Performance (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-performance-management">Revenue Performance Management (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-recognition">revenue recognition (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-lease-and-tax-accounting">Revenue, Lease and Tax Accounting (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revolution">Revolution (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revolution-analtyics">Revolution Analtyics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rightnow">RightNow (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rim">RIM (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/risk">Risk (37)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/risk-compliance-grc">Risk & Compliance (GRC) (17)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/risk-analytics">Risk Analytics (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/riversand">Riversand (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/roambi">Roambi (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/robotic-automation">robotic automation (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/robotic-finance">robotic finance (38)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/robotic-process-automation">Robotic Process Automation (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/roi">ROI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rpa">RPA (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rypple">Rypple (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sop">S&OP (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/saas">SaaS (27)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sab-miller">SAB Miller (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/saba">Saba (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sage">Sage (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sage-software">Sage Software (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales">Sales (169)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-and-operations-planning">Sales and Operations Planning (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-cloud">Sales Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-coaching">Sales Coaching (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-commission">Sales Commission (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-compensation">Sales Compensation (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-effectiveness">Sales Effectiveness (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-enablement">sales enablement (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-enablement-and-execution">Sales Enablement and Execution (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-engagement">Sales Engagement (25)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-force-automation">Sales Force Automation (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-forecasting">Sales Forecasting (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-operations">Sales Operations (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-performance">Sales Performance (446)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-performance-management">Sales Performance Management (77)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-performance-management-spm">Sales Performance Management (SPM) (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-planning">Sales Planning (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-planning-and-analytics">Sales Planning and Analytics (18)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-tax">Sales Tax (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-marketing-sales-performance-management-marke">Sales, Marketing, Sales Performance Management, Ma (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-sfa-spm-sales-performance-management-sales-c">Sales, SFA, SPM, Sales Performance Management, Sal (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/salescloud">SalesCloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/salesforce-com">Salesforce.com (58)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap">SAP (76)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-epm">SAP EPM (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-hana">SAP HANA (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-insider">SAP insider (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-lumira">SAP Lumira (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-netweaver">SAP NetWeaver (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-predictive-analytics">SAP predictive analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-teched">SAP TechEd (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sapphire">SAPPHIRE (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sarbanes-oxley">Sarbanes Oxley (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sas">SAS (26)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sas-institute">SAS institute (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sasb">SASB (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sase">SASE (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/savi">Savi (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/scm">SCM (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/scm-demand-planning">SCM Demand Planning (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/scout-rfp">Scout RFP (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/scribe-software">Scribe Software (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/search">Search (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sec">SEC (19)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sec-software">SEC Software (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/secfinops">SecFinOps (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/secops">SecOps (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/security">Security (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/security-posture">Security Posture (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sedar">SEDAR (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/self-service">Self-service (41)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/semantic-model">semantic model (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/service-supply-chain">Service & Supply Chain (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/service-cloud">Service Cloud (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/servigistics">Servigistics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sfa">SFA (24)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sfdc">SFDC (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sharepoint">SharePoint (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/shoretel">ShoreTel (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/siemens-enterprise-communications">Siemens Enterprise Communications (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/signal-demand">Signal Demand (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/silverpop">SilverPop (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/simba">Simba (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smart-financial-close">Smart Financial Close (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smart-manufacturing">Smart Manufacturing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smart-phones">Smart Phones (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smart-watches">Smart Watches (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smarter-analytics">Smarter Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smarter-workforce">Smarter Workforce (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smb">SMB (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/snaplogic">SnapLogic (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/snowfly">Snowfly (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/soa">SOA (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/soc">SOC (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social">Social (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-business">Social Business (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-collaboration">Social Collaboration (17)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-crm">Social CRM (128)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-dynamx">Social Dynamx (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-media">Social Media (365)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-media-analytics">Social Media Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-media-intelligence">Social Media Intelligence (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-recognition">Social Recognition (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/socialtext">SocialText (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sococare">SoCoCare (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/softscape">Softscape (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/software">Software (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/software-as-a-service">Software as a Service (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sourcing">sourcing (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sovereign-cloud">Sovereign Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sox">SOX (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spago-solutions">Spago Solutions (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spatial-data-quality">Spatial Data Quality (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/speech-analytics">Speech Analytics (177)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/splunk">Splunk (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spm">SPM (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spotfire">Spotfire (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spreadsheets">Spreadsheets (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spss">SPSS (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sql-h">SQL-H (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sqlstream">SQLstream (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/star-analytics">Star Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/statistics">Statistics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/stibo-systems">Stibo Systems (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/stratahadoop">Strata+Hadoop (56)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/streaming-analytics">Streaming Analytics (28)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/streaming-data">Streaming Data (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/streaming-data-events">Streaming Data & Events (32)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/subscriber-experience">Subscriber Experience (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/subscription-billing">Subscription Billing (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/subscription-management">Subscription Management (68)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/subscription-recurring-revenue-zuora">Subscription, Recurring Revenue, Zuora (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/successfactors">SuccessFactors (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sumo-logic">Sumo Logic (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sumtotal">SumTotal (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sumtotal-systems">SumTotal Systems (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sungard">Sungard (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sunsystems">Sunsystems (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supplier-relationship-management">supplier relationship management (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supply-chain">Supply Chain (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supply-chain-management">supply chain management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supply-chain-performance">Supply Chain Performance (253)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supply-chain-planning">Supply Chain Planning (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/surface">Surface (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/surveys">Surveys (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sustainability">Sustainability (38)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sustainability-and-esg">Sustainability and ESG (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sustainability-management">Sustainability Management (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/swordciboodle">SwordCiboodle (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sybase">Sybase (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sybase-iq">Sybase IQ (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sybase-mobile-industry">Sybase. Mobile Industry (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/syncsort">Syncsort (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/synygy">Synygy (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tableau">Tableau (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tableau-software">Tableau Software (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tablets">Tablets (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tagetik">Tagetik (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/talemetry">Talemetry (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/talend">Talend (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/talent-acquisition">Talent Acquisition (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/talent-generation">Talent Generation (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/talent-management">Talent Management (133)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/taleo">Taleo (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/talx">TALX (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tamr">Tamr (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tanner-labs">Tanner Labs (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax">Tax (35)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-compliance">tax compliance (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-department">tax department (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-planning">tax planning (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-software">Tax Software (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-datawarehouse">Tax-Datawarehouse (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-tax-provision-transfer-pricing">tax; tax provision; transfer pricing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tcm">TCM (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology">Technology (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology-innovation">Technology Innovation (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology-innovation-award">Technology Innovation Award (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology-spending">Technology Spending (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology-vendors">Technology Vendors (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/telephony">Telephony (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/teradata">Teradata (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/teradata-aster">Teradata Aster (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/text-analytics">Text Analytics (182)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tez">Tez (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/thomson-reuters-multinational">Thomson-Reuters multinational (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/threat-landscape">Threat Landscape (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/threat-management">Threat Management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tibco">Tibco (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tidemark">Tidemark (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/time-attendance">Time & Attendance (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tm">TM (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tm1">TM1 (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/topic">Topic (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/total-compensation-management">Total Compensation Management (46)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/total-rewards-management">total rewards management (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/towers-watson">Towers Watson (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/towers-watson-talent-management">Towers Watson Talent Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/training">Training (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/transcom">Transcom (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/transera">Transera (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/treasury">Treasury (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tribehr">TribeHR (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/trifacta">Trifacta (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/twitter">Twitter (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ucaas">UCaaS (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/uda">UDA (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ui">UI (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ukg">UKG (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ultimate">Ultimate (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ultimate-software">Ultimate Software (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/unanet-technologies">Unanet Technologies (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/uncategorized">Uncategorized (103)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/unica">Unica (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/unicorns">Unicorns (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/unified-communications">Unified Communications (83)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/unit4">Unit4 (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/upstream-works">Upstream Works (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/us-gaap">US-GAAP (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/us-gaap-accounting">US-GAAP accounting (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/usability">Usability (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/use-cases">Use Cases (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ux">UX (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/value-index">Value Index (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/value-added-tax">Value-Added Tax (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vantage-platform">Vantage platform (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/varicent">Varicent (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vat">VAT (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vendavo">Vendavo (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vendavo-price-pricing-optimization-revenue-custome">Vendavo, price, pricing, optimization, revenue, cu (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vendor-management-systems">Vendor Management Systems (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vendors">Vendor(s) (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/verint">Verint (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/verizon">Verizon (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vertex">Vertex (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vertical-solutions">Vertical Solutions (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vibe">Vibe (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/virtual-audit">virtual audit (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/virtual-close">virtual close (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/visi">Visi (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vistaar-technologies">Vistaar Technologies (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/visual-insight">Visual Insight (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/visualization">Visualization (17)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vitria">Vitria (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vivisimo">Vivisimo (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vmware">VMWare (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vocalcom">Vocalcom (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vocalcom-and-zeacom">Vocalcom and Zeacom (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/voice-analytics">Voice Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/voice-automation">voice automation (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/voice-of-the-customer">Voice of the Customer (260)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/voice-of-the-customer-interactive-intelligence">Voice of the Customer Interactive Intelligence (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/volly">Volly (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vovici">Vovici (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/vpi">VPI (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/wall-street-journal">Wall Street Journal (1)</a> </li> <li style="display:none;"> <a 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from Machines", "mainEntityOfPage": "https://blog.isg-research.net/2016/11/09/splunk-delivers-insights-from-machines/", "datePublished": "09/11/2016", "dateModified": "09/11/2016", "articleBody": "I recently attended .conf2016, Splunk’s seventh annual user conference. Splunk created the market for analyzing machine data (shorthand for machine-generated data), which consists of log files and event data from various types of systems and devices. Our big data analytics benchmark research shows that these are two of the most common sources of big data that organizations analyze. This market has proven to be fertile ground for Splunk, growing steadily with revenues more than doubling over the previous two fiscal years. Machine data is also the backbone for the Internet of Things (IoT) and operational intelligence, which form the basis of forthcoming benchmark research from Ventana Research. At the event, Splunk announced general availability of Splunk Cloud and Splunk Enterprise 6.5. The company also announced new versions of Splunk IT Service Intelligence, Splunk Enterprise Security and Splunk User Behavior Analytics. These new versions incorporate machine learning capabilities to help organizations analyze the massive volumes of machine data they collect with more advanced analytics and in a more automated manner. Machine learning has become a hot topic lately; it was also a popular subject at Strata+Hadoop World, as I wrote recently. The machine learning capabilities, which arose in part from Splunk’s July 2015 acquisition of Caspida, have been added to Splunk Cloud and Splunk Enterprise 6.5. Machine learning is a method used to develop predictive analytics without explicitly programming the models. In effect the algorithms are designed to sift through the data, learn from it and make predictions. With Version 6.5 Splunk also has simplified its data preparation capabilities and enhanced its user interface to appeal to more types of users. The company also offers tighter integration with Hadoop in this version. Storing historical data in Hadoop can help lower costs, and the Hadoop data can be combined with data in Splunk Enterprise using the Splunk query capability for a single unified interface. Splunk IT Service Intelligence (ITSI), an application built on the Splunk platform, provides a view of how critical IT services are operating as well as an environment in which to investigate and triage incidents when they occur. The latest release of ITSI, 2.4, includes machine learning capabilities to perform anomaly detection, identifying unusual system activity to help prevent outages and service degradations. The system can learn what the pattern of normal operations looks like and then establish thresholds for alerts that adapt to cyclical changes in usage. Adaptive alerts help reduce “alert fatigue” when so many alerts are issued that they overwhelm the recipients. Splunk Enterprise Security (ES), a security information and event management (SIEM) application, provides real-time monitoring of security threats and an environment to support incident response teams. Splunk ES 4.5, the latest release, provides a similar adaptive alerting feature based on machine learning as described above. ES 4.5 now includes the Glass Tables feature that has been available in ITSI, which allows users to create custom visualizations and KPIs. Splunk User Behavior Analytics (UBA) complements ES by analyzing longer periods of history to create a profile of normal user behavior and comparing it with peers to provide more advanced detection of security threats. UBA 3.0 incorporates more than 40 machine learning models, which cover a combination of streaming and batch analytic scenarios. Splunk in 2015 received the Technology Innovation Award for CIO for its innovation in advancing cybersecurity through these products. Splunk has followed a unique path. While a pioneer in the big data market, it built its products on a proprietary big data architecture rather than open source technologies as others did. In recent releases, however, it has broadened its support for Hadoop. Splunk focused on one subset of big data – machine data – and based much of its user interface around search. Rather than expand into the horizontal business intelligence market the company has chosen to tackle the IT service market and the SIEM market. This focus appears to have been successful so far. It’s hard to argue with its success. If you are looking for a way to manage and analyze the machine data in your organization, including IT service applications or enterprise security, I recommend you consider the offerings from Splunk. Regards, David Menninger SVP & Research Director Follow Me on Twitter @dmenningerVR and Connect with me on LinkedIn.", "image": { "@type": "ImageObject", "url": "http://research.ventanaresearch.com/hubfs/Ventana_Research_Sept_2016/images/shutterstock_314838419-1.jpg", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://blog.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.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": "Big Data Research Agenda and Trends are Bolder in 2015", "mainEntityOfPage": "https://blog.isg-research.net/2015/02/08/big-data-research-agenda-and-trends-are-bolder-in-2015", "datePublished": "07/02/2015", "dateModified": "07/02/2015", "articleBody": "Big data has become a big deal as the technology industry has invested tens of billions of dollars to create the next generation of databases and data processing. After the accompanying flood of new categories and marketing terminology from vendors, most in the IT community are now beginning to understand the potential of big data. Ventana Research thoroughly covered the evolving state of the big data and information optimization sector in 2014 and will continue this research in 2015 and beyond. As it progresses the importance of making big data systems interoperate with existing enterprise and information architecture along with digital transformation strategies becomes critical. Done properly companies can take advantage of big data innovations to optimize their established business processes and execute new business strategies. But just deploying big data and applying analytics to understand it is just the beginning. Innovative organizations must go beyond the usual exploratory and root-cause analyses through applied analytic discovery and other techniques. This of course requires them to develop competencies in information management for big data. Among big data technologies, the open source Hadoop has been commercialized by now established providers including Cloudera, Hortonworks and MapR and made available in the cloud through platforms such as Qubole, which received a Ventana Research Technology Innovation Award in 2014. Other big data technologies are growing as well; for example, use of in-memory and specialized databases also is growing like Hadoop in more than 40 percent of organizations, according to our big data integration benchmark research. These technologies have been integrated into databases or what I call hybrid big data appliances like those from IBM, Oracle, SAP and Teradata that bring the power of Hadoop to the RDBMS and exploit in-memory processing to perform ever faster computing. When placed into hosted and cloud environments these appliances can virtualize big data processing. Another new provider, Splice Machine, brings the power of SQL processing in a scalable approach that uses Hadoop in a cloud-based approach; it received a Ventana Research Technology Leadership Award last year. Likewise advances in NoSQL approaches help organizations process and utilize semistructured information along with other information and blend them with analytics as Datawatch does. These examples show that disruptive technologies still have the potential to revolutionize our approaches to managing information. Our firm also explores what we call information optimization, which assesses techniques for gaining full value from business information. Big data is one of these when used effectively in an enterprise information architecture. In this context the “data lake” analogy is not helpful in representing the full scope of big data, suggesting simply a container like a data marts or data warehouse. With big data, taking an architectural approach is critical. This viewpoint is evident in our 2014 Ventana Research Technology Innovation Award in Information Management to Teradata for its Unified Data Architecture. Another award winner, Software AG, blends big data and information optimization using its real-time and in-memory processing technologies. Businesses need to process data in rapid cycles, many in real time and what we call operational intelligence, which utilizes events and streams and provides the ability to sense and respond immediately to issues and opportunities in organizations that adapt to a data-driven culture. Our operational intelligence research finds that monitoring, alerting and notification are the top use cases for deployment, in more than half of organizations. Also machine data can help businesses optimize not just IT processes but business processes that help govern and control the security of data in the enterprise. This imperative is evident in the dramatic growth of suppliers such as Splunk, Sumo Logic and Savi Technology, all of which won Ventana Research Technology Innovation awards for how they process machine and business data in large volumes at rapid velocity. Another increasing trend in big data is presenting it in ways that ordinary users can understand quickly. Discovery and advanced visualization is not enough for business users who are not trained to interpret these presentations. Some vendors can present location and geospatial data on maps that are easier to understand. At the other end of the user spectrum data scientists and analysts need more robust analytic and discovery tools, including predictive analytics, which is a priority for many organizations, according to our big data analytics research. In 2015 we will examine the next generation of predictive analytics in new benchmark research. But there is more work to do to present insights from information that are easy to understand. Some analytics vendors are telling stories by linking pages of content, but these narratives don’t as yet help individuals assess and act. Most analytics tools can’t match the simple functionality of Microsoft PowerPoint, placing descriptive titles, bullets and recommendations on a page with a graphic that represents something important to these business professional who reads it. Deeper insights may come from advances in machine learning and cognitive computing that have arrived on the market and bring more science to analytics. So we strong potential for the outputs of big data, but they don’t arrive just by loading data into these new computing environments. Pragmatic and experienced professionals realize that information management processes do not disappear. A key one in this area is data preparation, which helps ready data sets for processing into big data environments. Preparing data is the second-most important task for 46 percent of organizations in our big data integration research. A second is data integration, which some new tools can automate. This can enable lines of business and IT to work together on big data integration, as 41 percent of organizations in our research are planning to do. To address this need a new generation of technologies came into their own in 2014 including those that received Ventana Research Technology Innovation Awards like Paxata and Tamr but also Trifacta. Yet another area to watch is the convergence of big data and cloud computing. The proliferation of data sources in the cloud forces organizations to managed and integrate data from a variety of cloud and Internet sources, hence the rise of information as a service for business needs. Ventana Research Technology Innovation Award winner DataSift provides information as a service to blend social media data with other big data and analytics. Such techniques require more flexible environments for integration that can operate anywhere at any time. Dell Boomi, MuleSoft, SnapLogic and others now challenge established data integration providers such as Informatica and others including IBM, Oracle and SAP. Advances in master data management, data governance, data quality and integration backbones, and Informatica and Information Builders help provide better consistency of any type of big data for any business purpose. In addition our research finds that data security is critical for big data in 61 percent of organizations; only 14 percent said that is very adequate in their organization. There is no doubt that big data is now widespread; almost 80 percent of organizations in our information optimization research, for example, will be using it some form by the end of 2015. This is partly due to increased use across the lines of business; our research on next-generation customer analytics in 2014 shows that it is important to improving understanding customers in 60 percent of organizations, is being used in one-fifth of organizations and will be in 46 percent by the end of this year. Similarly our next-generation finance analytics research in 2014 finds big data important to 37 percent of organizations, with 13 percent using it today and 42 percent planning to by the end of 2015. And we have already measured how it will impact human capital management and HR and where organizations are leveraging it in this area of importance. I invite you to download and peruse our big data agenda for 2015. We will examine how organizations can instrument information optimization processes that use big data and pass this guidance along. We will explore big data’s role in sales and product areas and produce new research on data and analytics in the cloud. Our research will uncover best practices that innovative organizations use not only to prepare and integrate big data but also more tightly unify it with analytics and operations across enterprise and cloud computing environments. For many organizations taking on this challenge and seeking its benefits will require new information platforms and methods to access and provide information as part of their big data deployments. (Getting consistent information across the enterprise is the top benefit of big data integration according to 39 percent of organizations.) We expect 2015 to be a big year for big data and information optimization. I look forward to providing more insights and information about big data and helping everyone get the most from their time and investments in it. Regards, Mark Smith CEO and Chief Research Officer", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/ventanaresearchlogo300px2-1.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Mark Smith", "url": "https://blog.isg-research.net/author/mark-smith", "sameAs": "http://www.linkedin.com/in/markallensmith" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.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": "Three Major Trends in New Discovery Analytics", "mainEntityOfPage": "https://blog.isg-research.net/2013/08/13/three-major-trends-in-new-discovery-analytics", "datePublished": "13/08/2013", "dateModified": "13/08/2013", "articleBody": "A few months ago, I wrote an article on the four pillars of big data analytics. One of those pillars is what is called discovery analytics or where visual analytics and data discovery combine together to meet the business and analyst needs. My colleague Mark Smith subsequently clarified the four types of discovery analytics: visual discovery, data discovery, information discovery and event discovery. Now I want to follow up with a discussion of three trends that our research has uncovered in this space. (To reference how I’m using these four discovery terms, please refer to Mark’s post.) The most prominent of these trends is that conversations about visual discovery are beginning to include data discovery, and vendors are developing and delivering such tool sets today. It is well-known that while big data profiling and the ability to visualize data give us a broader capacity for understanding, there are limitations that can be addressed only through data mining and techniques such as clustering and anomaly detection. Such approaches are needed to overcome statistical interpretation challenges such as Simpson’s paradox. In this context, we see a number of tools with different architectural approaches tackling this obstacle. For example, Information Builders, Datameer, BIRT Analytics and IBM’s new SPSS Analytic Catalyst tool all incorporate user-driven data mining directly with visual analysis. That is, they combine data mining technology with visual discovery for enhanced capability and more usability. Our research on predictive analytics shows that integrating predictive analytics into the existing architecture is the most pressing challenge (for 55% or organizations). Integrating data mining directly into the visual discovery process is one way to overcome this challenge. The second trend is renewed focus on information discovery (i.e., search), especially among large enterprises with widely distributed systems as well as the big data vendors serving this market. IBM acquired Vivisimo and is incorporating the technology into its PureSystems and big data platform. Microsoft recently previewed its big data information discovery tool, Data Explorer. Oracle acquired Endeca and has made it a key component of its big data strategy. SAP added search to its latest Lumira platform. LucidWorks, an independent information discovery vendor that provides enterprise support for open source Lucene/Solr, adds search as an API and has received significant adoption. There are different levels of search, from documents to social media data to machine data, but I won’t drill into these here. Regardless of the type of search, in today’s era of distributed computing, in which there’s a need to explore a variety of data sources, information discovery is increasingly important. The third trend in discovery analytics is a move to more embeddable system architectures. In parallel with the move to the cloud, architectures are becoming more service-oriented, and the interfaces are hardened in such a way that they can integrate more readily with other systems. For example, the visual discovery market was born on the client desktop with Qlik and Tableau, quickly moved to server-based apps and is now moving to the cloud. Embeddable tools such as D3, which is essentially a visualization-as-a-service offering, allow vendors such as Datameer to include an open source library of visualizations in their products. Lucene/Solr represents a similar embedded technology in the information discovery space. The broad trend we’re seeing is with RESTful-based architectures that promote a looser coupling of applications and therefore require less custom integration. This move runs in parallel with the decline in Internet Explorer, the rise of new browsers and the ability to render content using JavaScript Object Notation (JSON). This trend suggests a future for discovery analysis embedded in application tools (including, but not limited to, business intelligence). The environment is still fragmented and in its early stage. Instead of one cloud, we have a lot of little clouds. For the vendor community, which is building more platform-oriented applications that can work in an embeddable manner, a tough question is whether to go after the on-premises market or the cloud market. I think that each will have to make its own decision on how to support customer needs and their own business model constraints. Regards, Tony Cosentino VP and Research Director", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_predanalytics_predictive_analytics_obstacles-9.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://blog.isg-research.net/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Splunk Provides Operational Intelligence in the Cloud", "mainEntityOfPage": "https://blog.isg-research.net/2013/02/09/splunk-provides-operational-intelligence-in-the-cloud", "datePublished": "09/02/2013", "dateModified": "09/02/2013", "articleBody": "Splunk’s innovated ability to access and use machine data for targeted operational insights can help improve IT and enhance business operational efficiency. Its work to capitalize on big data was part of my last analysis, while my colleague Tony Cosentino looked at its focus on search and operational analytics. Splunk also was a recipient of the 2012 Ventana Research Technology Innovation Award for IT Performance for Splunk Enterprise. The latest Splunk release, version 5, advances its ability to provide operational intelligence to organizations by using data both from existing IT systems and in Hadoop. A new SDK offering supports Java, JavaScript, PHP and Python as part of its API. It can help developers get at data from social media and online applications and combine it with machine-generated data, which our research found to be the top data source according to 62 percent of organizations, followed by application data (53%) and historical data warehouse sources (43%). Splunk also now provides a cloud computing offering called Splunk Storm that helps companies take advantage of machine data in the cloud or on-premises. It lets users quickly create projects and analyze machine data with charts that can be shared with others. I had a chance to go through the new offering and found it to be simple and quick to analyze data and present analytics based on events, IP addresses and other machine data. Our latest benchmark research into operational intelligence found that activity or event monitoring is a top need in 62 percent of organizations; Splunk Storm can address this through its search and analyze approach. Splunk has made the pricing of the new offering simple. You select the storage volume you need in the cloud and get the pricing quickly. You can sign up for free and work with the product on data up to 1GB. Organizations can also analyze cloud data with the on-premises version of the product, but for many who need to quickly assess data without the hassle of using internal resources and systems, the software-as-a-service version is an easy way to get started. This is important, as the top barriers for operational intelligence are lack of resources (41%) and no budget (40%), and the on-demand approach is now preferred in 21 percent of organizations, which allows Splunk to address an expanding opportunity. With its on-premises product and its latest cloud computing offering, Splunk provides customers a good array of options. The company is moving quickly to add alerting and APIs that can be used to integrate to other offerings to upcoming Splunk Storm releases. Splunk has little competition when it comes to combining machine data with other data from business and IT to help organizations in cloud and enterprise approaches. It lets businesses harvest existing sources without having to establish a specialized data store first. Organizations should take a look at what Splunk is providing and how it can help address a class of operational and analytic needs across IT and business data. Regards, Mark Smith CEO & Chief Research Officer", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_2012_techaward_winner_logo1-4.jpg", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Mark Smith", "url": "https://blog.isg-research.net/author/mark-smith", "sameAs": "http://www.linkedin.com/in/markallensmith" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.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": "A Decade of Research at Ventana Research", "mainEntityOfPage": "https://blog.isg-research.net/2012/11/18/a-decade-of-research-at-ventana-research", "datePublished": "18/11/2012", "dateModified": "18/11/2012", "articleBody": "I’m happy to say that Ventana Research celebrated its tenth anniversary at our recent Business Technology Innovation Summit in San Jose at the Tech Museum. This location was fitting, since at the event we introduced and presented our first-ever Technology Innovation Awards and seventh annual Leadership Awards. If you did not get a chance to attend, we have the live webstream available for replay at no cost; thanks to Splunk for sponsoring this to let everyone enjoy the sessions. At our summit we discussed best practices organizations can employ to save time and resources when using technology across business processes. We also unveiled a series of new research studies on business technology innovation, next-generation business intelligence, integrated business planning, next-generation workforce management and customer service agent desktop. Our firm has strived for ten years to present research based on business and IT facts, rather than projecting analyst opinions based on handfuls of inquiries from IT-specific clients. We rely on primary research across business and IT as the foundation for our analysis and guidance, while most industry analyst firms provide opinions that do not represent the business priorities of organizations, because they research only IT. We continue to see the varying priorities of business and IT through our research, even where the alignment is not obvious. In our recent research on technology innovation, for instance, we found the number one factor driving change across business and IT is a business improvement initiative (60%) – and if you are not researching business, you cannot understand the dynamics of what organizations are doing to prioritize and select technology for business. The importance of independent research that covers business and IT is essential. I recently wrote about the skewed research in our industry and provided analysis about the misinformation on the projections that CMOs will outspend CIOs in technology. These situations point out the sad state of the technology analyst industry, which needs to do some serious self-policing of its actions and behavior. At our summit I was glad to bring forward some truth about technology innovation and the priorities of business and IT. Our new business technology innovation benchmark research uncovered some stark realities about what factors are most important for organizations to consider in technology in order to improve productivity and performance. Our research found analytics to be the top-ranked priority (39%), followed by collaboration (16%), mobile technology (15%), cloud computing (13%), big data (11%) and social media (11%). Organizations are using these critical technologies to improve results, and business improvement is the top factor driving change when businesses assess new technology. Many organizations are still working to address the largest barrier in taking on new technology, which is lack of resources (51%). I want to thanks the sponsors of the summit: IBM and SAP at the vanguard level, Ceridian and Datawatch at the pioneer level, and Peoplefluent, Planview and Saba at the ground-breaker level. I also thank the clients who over the last decade supported our mission to provide quality research and education to the industry. We also could not do this without the help of the partners who have helped us promote and syndicate our research. I thank everyone who has supported our mission to conduct research across business and IT in an independent and objective manner and provide facts and education to help advance businesses’ use of technology and gain the most value in the shortest period of time. I look forward to the next decade, and to continuing to deliver the most direct research and educational value to the market to help everyone use technology to its fullest value. Regards, Mark Smith CEO & Chief Research Officer", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_bti_br_whats_driving_change_to_technology_selection-12.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Mark Smith", "url": "https://blog.isg-research.net/author/mark-smith", "sameAs": "http://www.linkedin.com/in/markallensmith" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Splunk Bids to be King of Search and Operational Analytics", "mainEntityOfPage": "https://blog.isg-research.net/2012/09/14/splunk-bids-to-be-king-of-search-and-operational-analytics", "datePublished": "14/09/2012", "dateModified": "14/09/2012", "articleBody": "As I listened to the keynote address at, conf2012, the annual Splunk user conference, my initial impression was that the company was spreading itself too thin. The company highlighted four rather formidable areas of organizational focus: Enterprise 5.0, the company’s flagship data platform, which is now in beta; Development, which is support for building applications and integrating Splunk within the broader IT infrastructure; Content, the continued development of core applications and use cases in areas such as systems management and security; and Cloud, based on the recent Splunk Storm product, which targets a new class of customer – namely those developers who use services for everything. Is this broad-based vision a realistic goal, or merely an attempt to appease Wall Street pressure given the company’s relatively recent IPO? The key to answering this question lies in Splunk’s second objective, Development. Splunk sees its software as a platform upon which the developer community can build applications and create value. This business model has worked for such venerable companies as Microsoft, Apple, Amazon and Facebook. The key is gaining enough traction, and the main driver of such traction is Splunk’s extensible data fabric, with its 170+ REST-based interfaces and SDKs for Python, Java, JavaScript in beta, and PHP as a public preview. Such an approach allows Splunk to develop many use cases outside its core areas of systems and security, and cover the last mile to the business user with personal productivity tools such as Microsoft Excel and visual discovery tools such as Tableau. In talking with Splunk customers, I found a real passion for the product. Every customer I spoke with was either in the process of expanding their implementation or planning to do so. When asked about Splunk’s competition, customers couldn’t provide any quick answers; most said that there really was not any competition for Splunk. Some customers were going as far as having an autonomous Splunk team within their organization with an internal chargeback structure. This got me thinking about the fluidity of the software buying process within today’s organizations, as customer analytics and technology spending shifts toward LOB budgets. In this new age, Splunk is potentially a secret weapon of IT, since it gives the IT department the ability to go to other departments and show its business value. The trick for Splunk will be to quickly expand the use and usability of its product. Systems management and security have catapulted the company over the proverbial chasm of technology adoption, but in order to live up to expectations, it will have to address the needs of the business users – and Splunk should be able to do that, based on the presentations I saw and executive discussions I had at the conference. A sampling of innovative use cases includes: Expedia using Splunk to improve customer experience through increased response times, as well as optimize its search engine bidding process; Intuit using Splunk to increase customer intimacy by looking at actual site behavior rather than having to get the stated experience from an already frustrated customer; Comcast linking customer search behavior, location and billing information to customize content and usability; Bosch using Splunk to tie together sensor data from a network of medical devices to increase usability, satisfaction and uptime for in-home care patients. These are just a few public cases; I also spoke with large telecommunication companies and government organizations that are using Splunk in innovative ways to use data from systems at any velocity. At the end of the day, the killer application for Splunk is the same as it was for Google: search. It solves the same problem of expanding sets of distributed unorganized data, and it solves it in much the same way; but note that Splunk uses its own implementation of MapReduce. Our benchmark research into information management shows that data spread across too many applications and systems is the number-one barrier to managing data, and as Google did, Splunk helps to solve this problem with a relatively simple and elegant solution. The only real difference is that Splunk targets the business market instead of the consumer market, and the engine returns machine language instead of human language. Of course, the Google-like search function is a double-edged sword. The ease of use of search and iterative discovery analytics that Splunk provides its users can add tremendous value. At the same time, the interface is not a business user interface. It will need to expand further with data and visual discovery to provide stimulating presentation of the data, many business users or analysts will not be inclined to use the tool. This is one reason I’m excited to see the integration with Excel and visualization toolsets; as Splunk can roll out these tools, it should be able to grow share with business users. Splunk has made it easy to access the tool with a free download on their website. My recommendation for clients already using Splunk is to look at the expanded use cases above and see if any of these might apply to your organization. As you build your business case, don’t go to business managers (especially high-level ones) and show them a bunch of machine data. Splunk is definitely able to apply search and analytics on large volumes of data for what my colleague refers to them as big data machine for operational intelligence. Give them the right type of analytics and metrics and show them how Splunk helps solve issues such as the 360-degree view of the customer. For those currently without Splunk, there are many use cases including systems management and security along with customer interactions and experience in which it provides value and can combine systems and business data together dynamically. Regards, Tony Cosentino VP and Research Director", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_infomgt_barriers_to_information_management-14.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://blog.isg-research.net/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Splunk Provides Intelligence for Customer Analytics", "mainEntityOfPage": "https://blog.isg-research.net/2012/05/22/splunk-provides-intelligence-for-customer-analytics", "datePublished": "22/05/2012", "dateModified": "22/05/2012", "articleBody": "Recently my colleague Mark Smith wrote about Splunk and its latest technology supporting analytics for IT on machine data and providing operational intelligence. I wasn’t familiar with the company, which has focused on IT users and improving the performance of a company’s networks and IT systems. From a customer management perspective, these are of little interest unless they impact the customer experience; for example, if the website is down or the online banking system is unavailable. But in a follow-up briefing I learned that Splunk is increasingly playing in the business analytics market and has several user cases that relate directly to customers. I was intrigued by Splunk’s interesting use of the term “machine data.” I am a self-confessed technophobe, so I thought all data was machine-generated. Not so, according to Splunk, which can process data into three areas including: Business application data, such as transactional records, invoices and service case records Human-generated data, which includes interaction records such as email messages, IM logs, Web scripts, voice recordings and video Machine data, which is data generated by hardware or software systems on its operations. Splunk focuses on processing the last two types and integrates with the first to extract contextual data; for example, it can use an email address to look up additional customer data in a CRM system. When I heard this bells began ringing in my head, because I have written that a 360-degree view of the customer should be more extensive than most people think. The common perception is that it should include all available transaction data concerning customers (in Splunk’s terminology, business application data), but I think it should also include all available information about customer interactions (human-generated data) and any event data (machine data) that might impact the customer experience – for example, whether a cell within a mobile network is down, preventing customers from making calls, which in turn is likely to result in lots of calls to the contact center. I also have observed that while some vendors are getting close to producing a 360-degree view, no one is there yet. Splunk has an advantage here, because machine data is structured and often unstructured, and it has developed techniques that allow it to identify specific locations within a record as a defined field; for example, starting at location 100 in the script captured as a customer completes an online purchase, the next 20 characters represent the code of the product purchased. These definitions can be created automatically by analyzing multiple records, or users can define fields using tools within the product. These fields can be used to index records and thus to search for specific records to include in the analysis. Splunk’s product can also use fields as indexes to information from records in a business application; for example, a cell phone number could be used to look up the corresponding record in a CRM system to obtain additional customer information that can be included in the analysis. Analysis can also include data from multiple types of transactions, such as email, call recordings and Web scripts, allowing users to see, for example, all the different types of interactions a customer has had with a company – a technique that is often called cross-channel analytics. The analysis occurs in real time, and so could be used, for example, to show a contact center agent all the previous interactions a customer has made just prior to the current call. Splunk has user cases showing use of its product to track customer downloads from a website, the use of mobile messaging and the steps customers take to complete an online purchase. Although Splunk is not a well-recognized vendor in the customer analytics space, such applications show that it has the ability to combine business, interaction and machine (event) data to provide operational intelligence. In this context, that allows companies to better understand customer behavior and thus to proactively improve the customer experience. Regards Richard Snow – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://blog.isg-research.net/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Splunk: Big Data Machine for Operational Intelligence", "mainEntityOfPage": "https://blog.isg-research.net/2012/04/27/splunk-big-data-machine-for-operational-intelligence", "datePublished": "27/04/2012", "dateModified": "27/04/2012", "articleBody": "Splunk recently entered the financial markets as a publicly traded company (NASDAQ: SPLK) and also entered a new phase in its corporate growth. Splunk combines the power of search and discovery with analytics on data generated by IT systems, that they call machine data, and provide insight for a new generation of operational intelligence that helps everyone in IT including the CIO determine the efficiency of its systems that support business. The company has built a platform that can index data on a large scale (“big data”) for rapid analysis and search. They also through its analytics provide the ability to perform visual and data discovery which is critical to reduce the time to determining unknown issues in existing IT systems. This helps IT staff ascertain not just the performance but the efficiency of systems that operate on a 24-by-7 basis. Splunk’s software operates in real time, surpassing the traditional methods of applying business intelligence against a data warehouse – a practice that’s ineffective for use in IT, where time is not the CIO’s friend when it comes to understanding issues or opportunities for improvement. Splunk has grown rapidly, partly because it’s simple to download and try, and then to license for use in production. It has more than 3,300 licensed customers in 75 countries. The management team is led by CEO Godfrey Sullivan, who has experience and a track record at companies such as Hyperion. Where is Splunk finding its opportunity? IT organizations have been like the cobbler’s children who have no shoes. While they deliver applications and technology to business, IT departments seldom have time to analyze and optimize their own processes, systems, applications and projects. While this might sound counterintuitive, it is true. Almost seven years ago, I started investigating whether performance management being applied elsewhere in a business was occurring in IT. I discovered that CIOs lack critical tools to define goals and track the performance of their people and machines. Our IT Performance Management benchmark research identified lack of resources, budget and awareness as major contributing factors to this situation. It also showed that organizations that deploying appropriate tools were increasing IT effectiveness and supporting the needs of business more efficiently. Machine data or files were the top data source within 43 percent of IT organizations, and balancing loads between networks and servers, doing root cause analysis and doing impact analysis were key tasks in at least 52 percent of them. Splunk, which addresses this niche, has had significant growth over the last three years even though economic conditions have been shaky. Last year we came out with new benchmark research on IT Analytics that investigated analytics related to IT organizations managing systems that support business. This research found that only 15 percent of IT organizations are at the highest level of maturity in IT analytics in the key categories of people, process, information and technology; the bulk of organizations are still struggling to function effectively. Interestingly, 91 percent of IT organizations want their analytics to be simpler – understandably so, as 79 percent are using spreadsheets universally or regularly and more than half are dissatisfied with their existing technology. The top issues with current efforts are that information is not readily actionable (for 46%) and not adaptable or flexible to change (44%); many organizations have reports or files but can’t assess and act on the data. Splunk also addresses that need of more than half (52%) that are not able to easily get the data they need for IT analytics. Considering that IT spends more than two-thirds of its time in the analytics process in data-related tasks as opposed to actual analysis, Splunk’s ability to get to machine data and index it for search and analysis is a welcome sign. Usability was identified as the top-ranked evaluation criteria, followed by the need to search and navigate machine data, which is exactly what Splunk offers. Our analysis of Splunk’s latest release of software, version 4.3, found a series of advancements, including supporting access from tablets such as Apple’s iPad, support for data in cloud-based applications and the ability to operate in VMware environments, making it easier to deploy Splunk in the cloud. This version expands the enterprise scale of the platform, supporting more concurrent users and faster search. Users can preview machine data then start indexing against it for further discovery and analytics. These are all critical tasks as Splunk becomes a platform for harvesting machine data for search and discovery across the IT organization. Splunk must continue to expand its footprint with more collaborative capabilities to help IT understand issues and opportunities where analytics on the machine data are the starting point for dialogue and action. Introducing more collaborative capabilities and the ability to correlate data toward actions and notifications will help Splunk further differentiate its technology. Since our analysis, Splunk has continued to support new machine data environments, including Hadoop. It can run MapReduce queries against data in Hadoop and then bring the data into Splunk for analysis. Our benchmark research into Hadoop and Information Management found that users of Hadoop are most often focused on integrating machine data from application and Web logs with the events and network monitoring data that Splunk is designed to address. Hadoop users need to analyze data much faster than others, with 77 percent of organizations indicating they need analysis within a day and 25 percent within an hour. One challenge for organizations using Hadoop is staffing and training; Splunk addresses those obstacles with a tool that is easier to use than creating custom programs, and it provides real-time and integration features, each sought by two-thirds of organizations. The growth of Hadoop comes from the need to address big data needs but also the simple access to download the software and then use it which is also what Splunk does with its download to use its software. Splunk has a promising opportunity in the market, considering the size of IT spending on technology every year and the legacy of applications and systems that must be optimized for business use. Also, as IT organizations continue to advance their IT security and compliance and increase their use of cloud computing, the need not just to monitor but to analyze and act on issues and opportunities grows larger. Our last benchmark research on Operational Intelligence in IT found that IT has prioritized to manage IT performance through metrics in 71 percent of organizations, and more than half (58%) plan to improve their IT organization’s responsiveness. The research found more than half of organizations have at least 11 information sources to routinely interact with, which is part of why Splunk fits these needs on machine data. Splunk has little competition, with IT management software vendors like Computer Associates, Hewlett-Packard, IBM and Oracle providing little innovation or capabilities to address operational intelligence needs through discovery and analysis of machine data in IT. Eventually they or others will realize their shortcomings, but at that point I would expect to see Splunk be significantly larger with an expanded portfolio of capabilities for meeting a CIO’s need to truly become an information officer of his own IT organization. Regards, Mark Smith – CEO & Chief Research Officer", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Mark Smith", "url": "https://blog.isg-research.net/author/mark-smith", "sameAs": "http://www.linkedin.com/in/markallensmith" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script>  <script data-hs-allowed="true" src="/_hcms/forms/v2.js"></script> <script data-hs-allowed="true"> var options = { portalId: '2035844', formId: 'fa276fc9-9a16-4673-a644-1fcbedcc3c24', formInstanceId: '2842', pageId: '3884418273', region: 'na1', inlineMessage: "Thanks for subscribing!", rawInlineMessage: "Thanks for subscribing!", hsFormKey: "daadfc7672048786293dbe53796bbfa2", css: '', target: '#hs_form_target_module_1552944263900179', contentType: "listing-page", formsBaseUrl: '/_hcms/forms/', formData: { cssClass: 'hs-form stacked hs-custom-form' } }; 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