Data Federation/EII was a failure. But Data Virtualization is far more successful and becoming a critical information management capability at major companies. What context, technology and best practices shape DV success?

The pressure to deliver timely and agile data access to meet the new self-service minded business need for both BI and operational applications is getting higher. Your business partners and CIO want to leverage existing data assets more efficiently while adding diversity, complexity and volume with new internal and external sources. Data quality, security and governance are integral needs, not after-thoughts. Your budgets are not any bigger. You finally realize that traditional integration alone won’t cut it anymore.

Data Virtualization is mature and real. If you discard it as the same as past federation approaches, then you miss an opportunity to contribute value to your enterprise. On the other hand, you need to learn from past mistakes and new best practices of current generation Data Virtualization to ensure success.

Attend this session to learn:

• What is Data Virtualization Really? What are key differences and improvements over past approaches like Data Federation/EII which persist even today as embedded tools within BI?
• New Context and Need for Data Virtualization: How have data sources, technologies and most importantly business needs and use cases changed? Why is it important to consider Data Virtualization across Analytical, Operational and Data Management scenarios
• Five best practices for delivering agile data access and provisioning of virtualized data services
• Five most-common mistakes to avoid in Data Virtualization
• References to industry use cases where you can learn more