Data Virtualization: Solving Complex Data Integration Challenges

The data integration landscape has changed radically the past few years. What was once a relatively manageable problem of blending and unifying data from enterprise transaction systems has grown to encompass external data, Web data, clickstream data, end-user data, big data, cloud data, and more. New expectations for information-driven business agility further compound the complexities of modern data integration. The ETL-based data warehouse is no longer enough. Data virtualization is a core component of next-generation data integration architectures, techniques, and technology.

Get ready to expand your data integration capabilities, deliver business-speed information, and make the most of recent advances in data integration technology. Through a combination of lecture, exercises, and case study review you will learn how data virtualization works and how to position it in your data integration architecture and processes.

You Will Learn

Data virtualization definitions and terminology
Business case and technical rationale for data virtualization
Key concepts and foundational principles of virtualization–views, services, etc.
Data virtualization lifecycle, capabilities, and processes
How to extend the data warehouse with virtualization
How virtualization enables federation and enterprise data integration
How virtualization is applied for big data and cloud data challenges
How companies use virtualization to solve business problems and drive business agility

Geared To

BI, MDM, and data warehousing program and project managers
Data integration architects, designers, and developers
Data and technology architects

Technical resources.

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