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Next-Gen Data Integration: Enterprise Data Virtualization

Learn how data virtualization can help businesses meet changing needs, integrate data from multiple sources, and provide real-time insights. Explore use cases and recommendations from industry experts.

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Next-Gen Data Integration: Enterprise Data Virtualization

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  1. WEBINAREnterprise Data Virtualization: The Next-Generation Data Integration Technology Noel Yuhanna, Principal Analyst March 26, 2015. Call in at 12:55 p.m. Eastern time

  2. Agenda • Changing business needs requires a new data architecture. • What is data virtualization? How can it help? • New use cases • The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 • Recommendations

  3. Traditional data integration approaches are falling short when it comes to meeting new business requirements!

  4. It’s all about the data . . . Email News Banking Social network eCommerce Flight booking Stock market SMS/text

  5. Data is the new . . . It is now critical for business success.

  6. Data volume has grown — but it’s actually not about volume, variety, nor velocity — it’s about making sense of it.

  7. Finding hidden patterns that are meaningful to your business, delivering new insights and possibilities

  8. Today, only a small portion of available data is used. Currently utilized data 22% All data Available data

  9. What if we can flip the iceberg and tackle the problem? 78% Currently utilized data All data Available data

  10. Data is spread across data centers — often in various repositories and formats.

  11. What businesses need is connected and integrated data to make better and faster decisions.

  12. The age of the customer is driving the need for integrated data

  13. Loyalty How can you prevent members from churning? Look for patterns . . .

  14. Source: www.netflix.com How can you provide a perfect and individualized product recommendation? Integrated data from multiple sources Recommend

  15. Data requirements have changed More data . . . even more than we can handle Tougher compliance requirements Security concerns Demand for real time Growth of external sources Need for trusted data

  16. Agenda • Changing business needs requires a new data architecture. • What is data virtualization? How can it help? • New uses cases • The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 • Recommendation

  17. What is data virtualization? Forrester’s definition: An integration platform that orchestrates data in real time or near real time from disparate data sources, whether on-premises or cloud, into coherent self-service data services to support various use cases and workloads including extreme transactions, analytics, and predictive analytics

  18. Information fabric 3.0 reference architecture Source: August 8, 2013, “Information Fabric 3.0” Forrester report

  19. A logical view of information fabric 3.0 Source: August 8, 2013, “Information Fabric 3.0” Forrester report

  20. Building the global information fabric Source: August 8, 2013, “Information Fabric 3.0” Forrester report

  21. How is data virtualization different from traditional data integration approaches? • Delivers real-time data platform • Supports both analytics and transactions • Integrations with external sources, including cloud • Integrates with all types of data, including unstructured • Supports distributed in-memory data fabric

  22. How is data virtualization different from traditional data integration approaches? • Supports a canonical model to govern information delivery • Delivers data governance — lineage and access control • Integrates with big data, e.g., Hadoop, NoSQL • Delivers dynamic profiling, transformation, and quality • Uses standard and common protocols

  23. Agenda • Changing business needs requires a new data architecture • What is data virtualization? How does it help? • New use cases • The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 • Recommendations

  24. Data virtualization offers many use cases Customer personalization — 360-degree view Fraud detection Reference data Recommendation engines Real-time analytics

  25. Data virtualization offers many use cases (cont.) Actionable insights Big data apps Mobile apps Vertical-specific And others . . .

  26. Top data virtualization vendor landscape

  27. Agenda • Changing business needs requires new data architecture. • What is data virtualization? How can it help? • The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 • Recommendation

  28. Data virtualization systems integrators Accenture BearingPoint Computer Sciences Corp (CSC) HCL Technologies IBM Global Services Infosys TSC Tech Mahindra Wipro

  29. The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 Source: March 11, 2015, “The Forrester Wave™: Enterprise Data Virtualization, Q1 2015” Forrester report

  30. The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 Source: March 11, 2015, “The Forrester Wave™: Enterprise Data Virtualization, Q1 2015” Forrester report

  31. Agenda • Changing business needs requires new data architecture. • What is data virtualization? How can it help? • The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 • Recommendations

  32. Recommendations Data virtualization has many broad use cases — more than simple BI. Start with a few data source — mostly structured. Focus on in-memory data layer along with data virtualization.

  33. Recommendations (cont.) Be sure the solution complements your current ETL platform. Use Hadoop with data virtualization for very large data volume. Data virtualization is the next generation of data integration — it delivers a competitive edge and drives innovation and new opportunities.

  34. Noel Yuhanna +1 650.581.3807 nyuhanna@forrester.com Twitter: @nyuhanna

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