Book description
Making Data Integration Work: How to Systematically Reduce Cost, Improve Quality, and Enhance Effectiveness
Today’s enterprises are investing massive resources in data integration. Many possess thousands of point-to-point data integration applications that are costly, undocumented, and difficult to maintain. Data integration now accounts for a major part of the expense and risk of typical data warehousing and business intelligence projects--and, as businesses increasingly rely on analytics, the need for a blueprint for data integration is increasing now more than ever.
This book presents the solution: a clear, consistent approach to defining, designing, and building data integration components to reduce cost, simplify management, enhance quality, and improve effectiveness. Leading IBM data management expert Tony Giordano brings together best practices for architecture, design, and methodology, and shows how to do the disciplined work of getting data integration right.
Mr. Giordano begins with an overview of the “patterns” of data integration, showing how to build blueprints that smoothly handle both operational and analytic data integration. Next, he walks through the entire project lifecycle, explaining each phase, activity, task, and deliverable through a complete case study. Finally, he shows how to integrate data integration with other information management disciplines, from data governance to metadata. The book’s appendices bring together key principles, detailed models, and a complete data integration glossary.
Coverage includes
Implementing repeatable, efficient, and well-documented processes for integrating data
Lowering costs and improving quality by eliminating unnecessary or duplicative data integrations
Managing the high levels of complexity associated with integrating business and technical data
Using intuitive graphical design techniques for more effective process and data integration modeling
Building end-to-end data integration applications that bring together many complex data sources
Table of contents
- Title Page
- Copyright Page
- Contents
- Preface
- Acknowledgments
- About the Author
- Introduction: Why Is Data Integration Important?
- Chapter 1. Types of Data Integration
- Chapter 2. An Architecture for Data Integration
- Chapter 3. A Design Technique: Data Integration Modeling
- Chapter 4. Case Study: Customer Loan Data Warehouse Project
- Chapter 5. Data Integration Analysis
- Chapter 6. Data Integration Analysis Case Study
- Chapter 7. Data Integration Logical Design
- Chapter 8. Data Integration Logical Design Case Study
- Chapter 9. Data Integration Physical Design
- Chapter 10. Data Integration Physical Design Case Study
- Chapter 11. Data Integration Development Cycle
- Chapter 12. Data Integration Development Cycle Case Study
- Chapter 13. Data Integration and Data Governance
- Chapter 14. Metadata
- Chapter 15. Data Quality
- Appendix A. Chapter Exercise Answers
- Appendix B. Data Integration Guiding Principles
- Appendix C. Glossary
- Index
Product information
- Title: Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture
- Author(s):
- Release date: December 2010
- Publisher(s): IBM Press
- ISBN: 9780137085309
You might also like
book
The Data Model Resource Book, Volume 3: Universal Patterns for Data Modeling
This third volume of the best-selling "Data Model Resource Book" series revolutionizes the data modeling discipline …
book
Managing Data Orchestration and Integration at Scale
Why is data integration still a challenge today? And what does data orchestration mean? In this …
book
The Data Model Resource Book, Vol. 2: A Library of Data Models for Specific Industries
A quick and reliable way to build proven databases for core business functions Industry experts raved …
book
Designing for Product Strategy
How do you create a truly unique digital product that has potential to disrupt the market? …