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.
1. Chapter 1. Introduction to Data Virtualization 2. Chapter 2. Business Intelligence and Data Warehousing 3. Chapter 3. Data Virtualization Server: The Building Blocks 4. Chapter 4. Data Virtualization Server: Management and Security 5. Chapter 5. Data Virtualization Server: Caching of Virtual Tables 6. Chapter 6. Data Virtualization Server: Query Optimization Techniques 7. Chapter 7. Deploying Data Virtualization in Business Intelligence Systems 8. Chapter 8. Design Guidelines for Data Virtualization 9. Chapter 9. Data Virtualization and Service-Oriented Architecture 10. Chapter 10. Data Virtualization and Master Data Management 11. Chapter 11. Data Virtualization, Information Management, and Data Governance 12. Chapter 12. The Data Delivery Platform—A New Architecture for Business Intelligence Systems 13. Chapter 13. The Future of Data Virtualization 14. Bibliography 15. Index
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.
1. Chapter 1. Introduction to Data Virtualization 2. Chapter 2. Business Intelligence and Data Warehousing 3. Chapter 3. Data Virtualization Server: The Building Blocks 4. Chapter 4. Data Virtualization Server: Management and Security 5. Chapter 5. Data Virtualization Server: Caching of Virtual Tables 6. Chapter 6. Data Virtualization Server: Query Optimization Techniques 7. Chapter 7. Deploying Data Virtualization in Business Intelligence Systems 8. Chapter 8. Design Guidelines for Data Virtualization 9. Chapter 9. Data Virtualization and Service-Oriented Architecture 10. Chapter 10. Data Virtualization and Master Data Management 11. Chapter 11. Data Virtualization, Information Management, and Data Governance 12. Chapter 12. The Data Delivery Platform—A New Architecture for Business Intelligence Systems 13. Chapter 13. The Future of Data Virtualization 14. Bibliography 15. Index
