Mastering Data Warehouse Design Relational and Dimensional Techniques 1st edition by Claudia Imhoff, Nicholas Galemmo, Jonathan G. Geiger – Ebook PDF Instant Download/Delivery. 0471480921, 978-0471480921
Full download Mastering Data Warehouse Design Relational and Dimensional Techniques 1st Edition after payment
Product details:
ISBN 10: 0471480921
ISBN 13: 978-0471480921
Author: Claudia Imhoff, Nicholas Galemmo, Jonathan G. Geiger
- A cutting-edge response to Ralph Kimball’s challenge to the data warehouse community that answers some tough questions about the effectiveness of the relational approach to data warehousing
- Written by one of the best-known exponents of the Bill Inmon approach to data warehousing
- Addresses head-on the tough issues raised by Kimball and explains how to choose the best modeling technique for solving common data warehouse design problems
- Weighs the pros and cons of relational vs. dimensional modeling techniques
- Focuses on tough modeling problems, including creating and maintaining keys and modeling calendars, hierarchies, transactions, and data quality
Mastering Data Warehouse Design Relational and Dimensional Techniques 1st Table of contents:
PART ONE: CONCEPTS.
Chapter 1. Introduction.
Chapter 2. Fundamental Relational Concepts.
PART TWO: MODEL DEVELOPMENT.
Chapter 3. Understanding the Business Model.
Chapter 4. Developing the Model.
Chapter 5. Creating and Maintaining Keys.
Chapter 6. Modeling the Calendar.
Chapter 7. Modeling Hierarchies.
Chapter 8. Modeling Transactions.
Chapter 9. Data Warehouse Optimization.
PART THREE: OPERATION AND MANAGEMENT.
Chapter 10. Accommodating Business Change.
Chapter 11. Maintaining the Models.
Chapter 12. Deploying the Relational Solution.
Chapter 13. Comparison of Data Warehouse Methodologies.
People also search for Mastering Data Warehouse Design Relational and Dimensional Techniques 1st:
mastering data warehouse design relational and dimensional techniques
data warehouse design best practices
a data warehouse is composed of
mastering the data
5 principles of data warehousing