Analytic Discovery: Barrier or Opportunity to Gain Insight from Information

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Analytic Discovery: Barrier or Opportunity to Gain Insight from Information
 
Providing fancy business visualization and iterative discovery methods on data will not suffice everyone’s needs. A more definitive approach must be used to provide information in the right context and format to ensure the best possible value from growing reams of information assets from big data investments. Gleaning best practices from early adopters of big data analytics and information optimization was found in two research studies by Ventana Research in 2014. These research insights will help give attendees the real truth on how to use data and visual discovery and exploration software across business and IT roles that according to our research has become important to 48 percent of organizations.
 
This never seen before educational session by Mark Smith, CEO & Chief Research Officer and Tony Cosentino, VP & Research Director with exclusive research facts will allow you to be smarter and act more precisely on how to use discovery and exploration most effectively, and you will gain education to improve your efforts in the following ways:
 
1. Understand what and where to apply discovery and exploration
2. Gain best practices and who should use visual discovery
3. How to best use big data for advanced analytics
4. Why organizations are adopting visual discovery for big data
5. Determine where benefits are garnered by specific roles and personas.

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Analytic Discovery: Barrier or Opportunity to Gain Insight from Information

  1. 1. © 2014 Ventana Research1 © 2014 Ventana Research Analytic Discovery: Barrier or Opportunity to Gain Insight from Information Mark Smith, CEO & Chief Research Officer and Tony Cosentino, VP & Research Director @ventanaresearchvr In/ventanareseachventanaresearch.com
  2. 2. © 2014 Ventana Research2 © 2014 Ventana Research2 Ventana Research Value in Working with Ventana Research Research and Education • Members (250,000+) and Reach to 3m+ Professionals • Research and Reach across Finance, Ops and IT Benchmark Research • Conduct and Deliver Benchmark Research • Develop Analytic and Best Practice Assessments Technology Vendor Knowledge • Formalized Research Coverage of Technology Vendors • Deliver Research on Technology Impact to Business Business and Technology Expertise • Expertise Across Business and Technology • Understand Business Domain and Processes Ventana Research is the leading benchmark research and strategic advisory services firm. Our unparalleled analytic insights and best practices guidance are based on our rigorous research-based benchmarking, business, technology and best practices services. Our unique approach to covering people, process, information and technology in organizations across business and IT is unique to our analyst firm.
  3. 3. © 2014 Ventana Research3 © 2014 Ventana Research3 Industry Benchmark Services Benchmark Research  Reflects the current state and direction of business and technology best practices across business and IT.  Encompasses business and technology metrics.  Assess and measure people, process, information and technology dimensions.  Guidance on effectiveness of technology.  Targets areas for improvement.
  4. 4. © 2014 Ventana Research4 © 2014 Ventana Research4 Information Technology People Process Our Science and Value from Research Best and Worst Practices Clients and Feedback Benchmark Research Experience and Knowledge Buyer Research Value Index Research Technology Research Supplier Research Business & IT Coverage Our Research Agenda is driven by our analysts’ deep understanding of the buyer’s business requirements and our knowledge of vendor solutions and technology. All research builds on structured analysis of the people, process, information and technology dimensions that describe business issues.
  5. 5. © 2014 Ventana Research5 © 2014 Ventana Research5 State of the Market
  6. 6. © 2014 Ventana Research6 © 2014 Ventana Research6 Business Intelligence Mature Market: • Dashboards • Reports • Query and Present • Analysis • Spreadsheets
  7. 7. © 2014 Ventana Research7 © 2014 Ventana Research7 Business Analytics Evolving Discipline: • Empowering analysts to perform analytics more effectively. • Apply Predictive Analytics (64%), take action on outcomes (48%) and present data visually (45%) are top capabilities requested. • Perform faster analysis (49%) is advantage of visualizing big data. Source: Ventana Research Big Data Analytics Benchmark Research
  8. 8. © 2014 Ventana Research8 © 2014 Ventana Research8 1. Business can not buy without IT 2. Data scientists control data / analytics buying 3. Analytics is responsibility of IT 4. Business intelligence will resolve all needs 5. Spreadsheets are not heavily used today 6. Needs addressed by dashboards & reports 7. Mobile access to BI is not important 8. Cloud computing is not important to BI 9. Visual and data discovery is next BI 10. Location is just a pretty picture on data Myths on BI and Business Analytics
  9. 9. © 2014 Ventana Research9 © 2014 Ventana Research9 Understanding Analytical Discovery
  10. 10. © 2014 Ventana Research10 © 2014 Ventana Research10 Analytic Discovery: Approaches Spectrum of Methods: • Event: Leveraging streams of events from applications, systems and machine data. • Data: Utilizing data to better understand the good, bad and ugly of what is analyzed. • Visual: Presenting the data in a simple and sophisticated manner through simple to sophisticated methods. • Information: Harvesting the content and text in our enterprise to enhance the presentation and insights.
  11. 11. © 2014 Ventana Research11 © 2014 Ventana Research11 Changing Priorities: User and Buyer Criteria Related research: •Usability and Functionality are the most important product and vendor considerations in selecting software to design and deploy big data and business analytics. Usability Functionality Reliability Manageability Adaptability TCO/ROI Validation Category % selecting Very Important 63% 50% 50% 42% 32% 31% 20% Source: Ventana Research Big Data Analytics Benchmark Research User experience and simplicity is most critical.
  12. 12. © 2014 Ventana Research12 © 2014 Ventana Research12 Barrier to Analytical Discovery Largest areas where time is wasted with analysts: Preparing Data for Analysis 47% Reviewing data for quality and consistency 45% Waiting for analysts to assemble data 39% Interpreting information for use by others 33% Waiting for data and information from IT 32% Source: Ventana Research Information Optimization Benchmark Research
  13. 13. © 2014 Ventana Research13 © 2014 Ventana Research13 Who Should Use Analytical Discovery
  14. 14. © 2014 Ventana Research14 © 2014 Ventana Research14 Business Analytics: Usage Personas These are common types of roles and responsibilities: Information Consumers • Digest information and perform basic interactions on data and analytics. Knowledge Workers • Utilize and interact with analytics and data to drive actions and decisions. Designers • Enable the design and use of information and analytics across roles. Analysts • Engage with data and design analytics for insights and actions. Data Geeks • Enable data to be accessed and exploited.
  15. 15. © 2014 Ventana Research15 © 2014 Ventana Research15 Important Analyst and End User Capabilities 39% 37% 34% 30% 24% Most Important analyst capabilities: Extract information Design and Integratee metrics Develop policies for info access Perform analytics to determine interest Provide search capabilities Source: Ventana Research Information Optimization Benchmark Research 36% 27% 25% 25% Most Important end user capabilities: Drill down into information Provide search capabilities Collaborate on Information Navigate and retrieve information Access applications via a mobile device Source: Ventana Research Information Optimization Benchmark Research 37%
  16. 16. © 2014 Ventana Research16 © 2014 Ventana Research16 Big Data Analytics Skills Gap Related research facts: • Most have implemented big data analytics with custom builds (54%), but in the future the largest percentage plan to purchase dedicated or packaged software (44%). • Organizations are more successful if led by experts such as data scientists (88%) or consultants (86%) rather than LOB (78%) or IT (73%). Big data analytics skills available versus needed: Source: Ventana Research Big Data Analytics Benchmark Research 73% 47% 34% 35% 36% 35% Business skills 76% 42% 58% 31% 28% 57% Needed Available Statistical skills Spreadsheet skills Mathematical skills Visual analysis skills SQL skills
  17. 17. © 2014 Ventana Research17 © 2014 Ventana Research17 How to Use Big Data for Analytics
  18. 18. © 2014 Ventana Research18 © 2014 Ventana Research18 Big Data: Technological Choices Appliances Flat Files In-Memory Hadoop NoSQL RDBMS Specialized DB
  19. 19. © 2014 Ventana Research19 © 2014 Ventana Research19 Big Data: Adoption Growing Source: Ventana Research Information Optimization Benchmark Research 94% of organizations intend to use big data. 23% have used for more than a year. 56% have started deploying in past 12 months or will begin to use within the next 12 months. 45% of organizations are either using Hadoop or plan to use Hadoop over the next year. Another 26% are still evaluating the technology.
  20. 20. © 2014 Ventana Research20 © 2014 Ventana Research20 Big Data Analytics: Important Types Related research facts: •Predictive analytics ranks number five in analytic capabilities currently available in the organization (57%), lagging more descriptive approaches of query and reporting (74%). •Top analytic methods are pivot tables (46%), classification (39%), and clustering (37%). •Visual analytics is used for contextual understanding (48%) and root cause analysis (40%). Source: Ventana Research Big Data Analytics Benchmark Research 18%47% Advanced / predictive 26%13% Descriptive analytics 20%16% Real-time analytics 13%9%Visual Analytics In-database analytics In-memory analytics SecondFirst Importance 15%9% 7%4%
  21. 21. © 2014 Ventana Research21 © 2014 Ventana Research21 Current Analytic Methods for Big Data Related research facts: • Current analytic methods focus around exploratory analytic methods reflected by predictive capabilities currently available in the organization (57%), lagging more descriptive approaches of query and reporting (74%). 46% 39% 37% 35% 32% Methods currently in use for big data analytics Pivot Tables Classification or Decision Trees Clustering Linear Regression Time Series Analysis Source: Ventana Research Big Data Analytics Benchmark Research
  22. 22. © 2014 Ventana Research22 © 2014 Ventana Research22 Why Adopt Analytic Discovery
  23. 23. © 2014 Ventana Research23 © 2014 Ventana Research23 Business Wants Insights and Action Choices: • Less data and more insights to act on for improving. • Less visualization and more interpretation of what is relevant. • Gain value from Big Data investments. • More dialogue and relevant collaboration among business.
  24. 24. © 2014 Ventana Research24 © 2014 Ventana Research24 Need to Access and Analyze Big Data Related research facts: • IT places more emphasis on finding patterns in Hadoop (60% vs 51%) and doing real- time stream processing (48% vs 43%) while business users place emphasis on analyzing data from all sources, not just one (80% vs 72%). • Business users take the view that there are multiple versions of the truth and up to the user to understand the data and business context (40% vs 32%). 76% 56% 55% 44% 40% How organizations define big data analytics Analyze data from all sources, not just one Find patterns in large, diverse data sets in Hadoop Analyze all data, not just a sample of it Do real-time processing on stream of data Visualize in seconds large, structured data sets Source: Ventana Research Big Data Analytics Benchmark Research
  25. 25. © 2014 Ventana Research25 © 2014 Ventana Research25 The End Game: Time-to-Value (TTV) Must provide: • Give business a short or medium term ROI. • Focus on business outcomes, not just technology. • Show smarter use of resources and time with savings that are explicit. • Provide specific competitive advantage or operational efficiency gains. • Unlock the value of data for business insights and action.
  26. 26. © 2014 Ventana Research26 © 2014 Ventana Research26 Benefits of Adoption
  27. 27. © 2014 Ventana Research27 © 2014 Ventana Research27 Advantages of Visualizing Big Data Related research facts: •Perform faster analysis followed by Understand context better are considered to be the key analytical advantages of visualizing big data. •Visualization provides part of the analytical needs but not all of them. 49% 48% 40% 40% 35% Advantages of Visualizing Big Data : Perform Faster Analysis Understand Context Better Perform Root Cause Analysis Display Multiple Result Sets Deal With Outliers Source: Ventana Research Big Data Analytics Benchmark Research
  28. 28. © 2014 Ventana Research28 © 2014 Ventana Research28 Differing Benefits of Big Data Analytics Related research facts: • 21% of organizations have improved their business processes significantly with big data analytics. • Prior to implementation response to opportunities and threats, improving efficiency and improved customer experience were most mentioned. 24% 18% 17% 10% 6% Benefits of Big Data analytics post implementation: Better communication and knowledge sharing Better management and alignment of business Gained competitive advantage Faster response to opportunities and threats Decreased time to market Source: Ventana Research Big Data Analytics Benchmark Research
  29. 29. © 2014 Ventana Research29 © 2014 Ventana Research29 Best Practices in Analytical Discovery Start with benefits including time-to-value, communication and knowledge sharing, and increased productivity. Address personas and responsibilities with right analytics for business and time allowed. Determine specific data sources to integrate including transactional, engagement, demographic and attitudinal. Consider usability, manageability and reliability with analytics to gain efficiencies and competitive advantage. 1 2 3 4
  30. 30. © 2014 Ventana Research30 © 2014 Ventana Research30 Questions? Twitter @ventanaresearch @marksmithvr @tonycosentinovr LinkedIn http://www.linkedin.com/company/ventana-research Blog http://blog.ventanaresearch.com http://marksmith.ventanaresearch.com http://tonycosentino.ventanaresearch.com
  31. 31. © 2014 Ventana Research31 © 2014 Ventana Research Analytic Discovery: Barrier or Opportunity to Gain Insight from Information Mark Smith, CEO & Chief Research Officer and Tony Cosentino, VP & Research Director @ventanaresearchvr In/ventanareseachventanaresearch.com

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