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Accelerating Fast Data Strategy with Data Virtualization

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"Information from the past won't support the insights of the future - businesses need real-time data," said Forrester Analyst Noel Yuhanna. In this presentation, he explains the challenges of latent data faced by business users, the need to accelerate fast data strategy using data virtualization, and the implications of such strategy.

This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/a2xNyZ.

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Accelerating Fast Data Strategy with Data Virtualization

  1. 1. Accelerating Fast Data Strategy With Data Virtualization Noel Yuhanna, Principal Analyst
  2. 2. © 2016 Forrester Research, Inc. Reproduction Prohibited 2 Data bottlenecks are creating business bottlenecks that’s impacting growth and innovation!
  3. 3. © 2016 Forrester Research, Inc. Reproduction Prohibited 3 Currency Oil Bacon Digital business is all about the data… But what if your data is slow that’s not being utilized for analytics or is not being used in a timely manner? Data is the new…
  4. 4. Challenge Today business users think of analytics as a set of boring reports and dashboards … they don’t want yesterdays data tomorrow!
  5. 5. of enterprise data in used for analytics…. 12%Only Source: Forrester’s “The Forrester Wave: Big Data Hadoop Solutions”, report Reality
  6. 6. © 2016 Forrester Research, Inc. Reproduction Prohibited 6 Top data challenges seen across industries are slowing growth and revenue › It takes longer to measure business performance because of aging data architectures › It takes longer to provide insights for operational decision making because of lack of self-service › It takes longer to get intelligence into business processes because data is in silos › It takes longer to make decisions because of complexity in systems and processes.
  7. 7. © 2016 Forrester Research, Inc. Reproduction Prohibited 7 Real-time has been evolving over the years but has been challenging to deploy.. Stock market Ticketing Fraud DetectioneCommerceBanking
  8. 8. © 2016 Forrester Research, Inc. Reproduction Prohibited 8 Businesses want real-time access to data. What’s are the drivers? › Mobile devices – we need data now! › Competitive pressure – to act more quickly › Pressure from businesses (LOB) - to support real-time › New insights, advanced analytics – real-time BI › Global business – that needs global real-time access › IOT Applications – sensors, devices . .and lower cost.
  9. 9. We are moving from IT to Business Technology (BT).. MIS IT BT Self-service Real-time Automation Limited data Digital business Trends Lots of data Batch
  10. 10. © 2016 Forrester Research, Inc. Reproduction Prohibited 10 TREND – The need for Fast Data Real-time Mostly Batch FAST DATA
  11. 11. © 2016 Forrester Research, Inc. Reproduction Prohibited 11 What is Fast Data? Fast Data is combining Systems of Engagement (batch) and Systems of Record(Real-time) together quickly to support new next-generation business analytics. Systems of engagement (SOE) • Mobile, web, and smart devices • Frequent changes • Delight clients • Delivered frequently Systems of record (SOR) • Stable requirements • Highly transactional • Less change • Delivered infrequently Forrester estimates that 20% of all data in an enterprises is Fast Data, and that’ll double over the next five years. Fast Data Traditional DataReal-time data
  12. 12. © 2016 Forrester Research, Inc. Reproduction Prohibited 12 Road Map For Fast Data Strategy
  13. 13. © 2016 Forrester Research, Inc. Reproduction Prohibited 13 Four-Phase road map to help deliver your Fast Data strategy 1. Phase 1. Remove insights bottlenecks – migrate away from slow-moving batch processing, and focus on automation. 2. Phase 2. Remove operational bottlenecks to scale. Use real- time streaming and embedded analytics, and decision making 3. Phase 3. Enable self-service data platform. Focus on self- service tools that enable end-users to access data themselves. 4. Phase 4. Use technologies such as Data virtualization to accelerate Fast Data Strategy faster time-to-value.
  14. 14. © 2016 Forrester Research, Inc. Reproduction Prohibited 14 What is data virtualization Forrester’s definition: The integration of any data in real time or near real time from disparate data sources, whether internal or external, into coherent data services that support business transactions, analytics, predictive analytics, and other workloads and patterns
  15. 15. © 2016 Forrester Research, Inc. Reproduction Prohibited 15 Data Virtualization supports real-time platform › Integrates disparate data sources in real time or near-real time to meet demands for analytics and transactional data. › Integrates internal and external data sources such as Hadoop, NoSQL, and enterprise DW platforms.. social › It supports both structured and unstructured data sources. › It delivers a self-service trusted data platform to support simplified data access across the enterprise. › It is agile to support new sources, and deliver new next- generation insights need for business to succeed.
  16. 16. © 2016 Forrester Research, Inc. Reproduction Prohibited 16 Data virtualization deployment strategy ERP CRM Text Logs Sensors Audio Social Video Data Lake Hadoop Data Warehouse Data Virtualization BI Analytics Predictive Manage Integrate Deliver IOT Apps Reporting
  17. 17. © 2016 Forrester Research, Inc. Reproduction Prohibited 17 Recommendations › In the era of big data, you need to look beyond traditional data architectures to succeed and gain competitive advantage. › Fast data strategy needs to be on your roadmap, focusing on making data available more quickly to business users and decision makers. › Look at accelerating batch and slow-moving data, to support new business insights to grow and innovate. › Look at data virtualization solution that can provide integration, security, provisioning and automation to support your fast data strategy.
  18. 18. © 2009 Forrester Research, Inc. Reproduction Prohibited Thank you! Noel Yuhanna www.forrester.com Twitter: @nyuhanna

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