Design Guidelines for Data Virtualization
This chapter describes a number of guidelines for designing a business intelligence system based on data virtualization. These design guidelines are based on experiences from real-life projects in which data virtualization was deployed. They address the following questions:
• Where and how should incorrect data be handled?
• How many levels of virtual tables should be defined?
• At which level should data from multiple systems be integrated?
• Should virtual tables be normalized?
• How can access to production systems be made more efficient?
• How is the archiving of data designed?
Note: Because this book doesn’t focus on one particular data virtualization product, this ...