- First independent book on data virtualization that explains in a product-independent way how data virtualization technology works.
- Illustrates concepts using examples developed with commercially available products.
- Shows you how to solve common data integration challenges such as data quality, system interference, and overall performance by following practical guidelines on using data virtualization.
- Apply data virtualization right away with three chapters full of practical implementation guidance.
- Understand the big picture of data virtualization and its relationship with data governance and information management.
Data virtualization can help you accomplish your goals with more flexibility and agility. Learn what it is and how and why it should be used with Data Virtualization for Business Intelligence Systems. In this book, expert author Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. You’ll learn the difference is between this new form of data integration and older forms, such as ETL and replication, and gain a clear understanding of how data virtualization really works. Data Virtualization for Business Intelligence Systems outlines the advantages and disadvantages of data virtualization and illustrates how data virtualization should be applied in data warehouse environments. You’ll come away with a comprehensive understanding of how data virtualization will make data warehouse environments more flexible and how it make developing operational BI applications easier. Van der Lans also describes the relationship between data virtualization and related topics, such as master data management, governance, and information management, so you come away with a big-picture understanding as well as all the practical know-how you need to virtualize your data.
Data warehouse architects, Business intelligence experts, Database designers, Database administrators, BICC employees, Data analysts; as well as architects, designers and developers involved in/responsible for data integration projects, including SOA and EAI experts.