ESG Research Report Snapshot Big Data and Integrated Infrastructure Aug 2012
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ESG Research Report Snapshot Big Data and Integrated Infrastructure Aug 2012

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Overview of finding from Enterprise Strategy Group (ESG) finding of survey about Big Data

Overview of finding from Enterprise Strategy Group (ESG) finding of survey about Big Data

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ESG Research Report Snapshot Big Data and Integrated Infrastructure Aug 2012 ESG Research Report Snapshot Big Data and Integrated Infrastructure Aug 2012 Presentation Transcript

  • TM Enterprise Strategy Group | Getting to the bigger truth. The Convergence of Big Data and Integrated Infrastructure Research Report Snapshot Evan Quinn, Senior Principal Analyst July, 2012©2012 Enterprise Strategy Group
  • Survey Overview Respondents • 399 IT and LoB decision makers responsible for their organization’s BI/analytics, data management and related infrastructure environments • 22% line-of-business; 32% “analysts” including data scientists, business analysts, data analysts and report administrators Organizations • 54% enterprise (>999 employes), 46% midmarket (100-999 employees) • North America • All primary vertical industries represented except tech:  18-to-6% range: manufacturing, financial services, government, comms/media, business services, retail/wholesale, healthcare Questionnaire • A wide sweep across big data, analytics, data management, infrastructure • Subjects: Business/IT priorities, meaning/impact of Big Data, data volume and diversity, integration techniques, analytics solutions, storage impact© 2012 Enterprise Strategy Group 2
  • Research Objective Snapshot Key Survey Research Questions • How important is the enhancement of analytics capabilities relative to an organization’s business and IT priorities? • What is associated with the term “big data?” • What is the current and planned usage of Hadoop MapReduce • Regarding largest data sets used for analytics:  What is the largest size, how many sources, what are the types, how frequently updated, are there geographic distribution challenges? • What tools are used for data integration in relation to big data? • What data analytics and/or processing challenges do organizations face? • What data analytics platforms have been/will be deployed for big data • What are key data management features needed to support analytics • What storage technologies are used to support analytics; which are most pervasive and how will this change going forward? • How much downtime can be tolerated for analytics? • What data protection technologies are in place to support analytics and related processing?© 2012 Enterprise Strategy Group 3
  • Key Finding: Analytics a Top 5 Priority Relative to all of your organization’s business and IT priorities over the next 12-18 months, how would you rate the importance of enhancing data processing and analytics activities? (Percent of respondents, N=399) Importance of enhancing data processing and analytics activities relative to all business priorities Importance of enhancing data processing and analytics activities relative to all IT priorities 50% 45% 45% 40% 38% 35% 30% 28% 25% 21% 20% 18% 19% 15% 11% 10% 10% 6% 5% 4% 1% 0% Our most important One of our top 5 One of our top 10 One of our top 20 Not among our top 20 Don’t know priority priorities priorities priorities priorities Source: ESG Research Report, The Convergence of Big Data Processing and Integrated Infrastructure, July 2012© 2012 Enterprise Strategy Group 4
  • Key Finding: Strong Demand for New Analytics Platforms Does your organization have plans to deploy a new data analytics platform in the next 12-18 months in support of its fastest growing data set? (Percent of respondents, N=399) Dont know, 14% Yes, 39% No, 46% Source: ESG Research Report, The Convergence of Big Data Processing and Integrated Infrastructure, July 2012© 2012 Enterprise Strategy Group 5
  • Key Finding: Hadoop MapReduce Heating Up How would you rate your organization’s interest in implementing a MapReduce framework to address data analytics challenges? (Percent of respondents, N=399) We currently use MapReduce technology to support our largest data 2% set We currently use MapReduce technology in a limited production 2% capacity (e.g., small data analytics tasks) We are currently testing MapReduce technology 5% We plan to deploy MapReduce technology in the next 12-18 months 1% Very interested 20% Somewhat interested 32% Not at all interested 12% Not familiar with MapReduce framework technology 18% Don’t know 8% 0% 5% 10% 15% 20% 25% 30% 35% Source: ESG Research Report, The Convergence of Big Data Processing and Integrated Infrastructure, July 2012© 2012 Enterprise Strategy Group 6
  • Conclusions to Big Data and Integrated Infrastructure1. Organizations view improving analytics capabilities as critical2. “Big Data” means dealing with very large data sets (57%)3. No clear leaders for big data commercial analytics have emerged • Unlikely this will change over the next 12-18 months, but demand and interest for new analytics platforms is strong at 39% • The high cost and difficulties of using existing analytics solutions for big data is the primary driver towards new analytics related purchases4. Security, data integration and data quality are the biggest hurdles5. Improved business agility is the most sought-after benefit for deploying a new analytics solution6. Hadoop MapReduce adoption has been limited to date, but • There will be a strong shift to commercial distributions of Hadoop MapReduce based solutions among the next wave of adopters; <40% don’t know or have no interest • 17% are interested in public cloud-based big data solutions7. Big data analytics infrastructures should excel at availability, performance/bandwidth and information management© 2012 Enterprise Strategy Group 7
  • IT Advisory for Big Data Analytics 1. Small promises, small wins Look for vendors who want to help evolve your organization towards big data and are willing to leverage existing resources; avoid those who promise big results or say that it will be easy; big data requires an educational investment for IT and most business/data analysts 2. Your current vendor(s) may have your best big data answer Despite the “newness” of big data, many established database and analytics vendors have stayed abreast of the technology; if you like your current vendor they may be your best option 3. Improve overall data management practices for big data If your current practices around data integration, governance, security and information management are lacking, big data projects will expose those weaknesses© 2012 Enterprise Strategy Group 8