Mastering Data Warehouse Design : Relational and Dimensional Techniques, Pape...

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Condition:
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Last updated on 05 Oct, 2025 08:47:36 BSTView all revisionsView all revisions

Item specifics

Condition
Good
A book that has been read, but is in good condition. Minimal damage to the book cover eg. scuff marks, but no holes or tears. If this is a hard cover, the dust jacket may be missing. Binding has minimal wear. The majority of pages are undamaged with some creasing or tearing, and pencil underlining of text, but this is minimal. No highlighting of text, no writing in the margins, and no missing pages. See the seller’s listing for full details and description of any imperfections. See all condition definitionsopens in a new window or tab
Seller notes
“May show signs of wear, highlighting, writing, and previous use. This item may be a former library ...
Book Title
Mastering Data Warehouse Design : Relational and Dimensional Tech
ISBN
9780471324218
Category

About this product

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0471324213
ISBN-13
9780471324218
eBay Product ID (ePID)
2355091

Product Key Features

Number of Pages
456 Pages
Language
English
Publication Name
Mastering Data Warehouse Design : Relational and Dimensional Techniques
Publication Year
2003
Subject
Databases / Data Warehousing
Type
Textbook
Subject Area
Computers
Author
Nicholas Galemmo, Claudia Imhoff, Jonathan G. Geiger
Format
Trade Paperback

Dimensions

Item Height
1.1 in
Item Weight
25.6 Oz
Item Length
9 in
Item Width
7.2 in

Additional Product Features

Intended Audience
Trade
LCCN
2003-010879
Dewey Edition
21
Illustrated
Yes
Dewey Decimal
005.74
Table Of Content
Acknowledgments. About the Authors. 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. Glossary. Recommended Reading. Index.
Synopsis
At last, a balanced approach to data warehousing that leverages the techniques pioneered by Ralph Kimball and Bill Inmon Since its groundbreaking inception, the approach to understanding data warehousing has been split into two mindsets: Ralph Kimball, who pioneered the use of dimensional modeling techniques for building the data warehouse, and Bill Inmon, who introduced the Corporate Information Factory and leads those who believe in using relational modeling techniques for the data warehouse. Mastering Data Warehouse Design successfully merges Inmon's data ware- house design philosophies with Kimball's data mart design philosophies to provide you with a compelling and complete overview of exactly what is involved in designing and building a sustainable and extensible data warehouse. Most data warehouse managers, designers, and developers are familiar with the open letter written by Ralph Kimball in 2001 to the data warehouse community in which he challenged those in the Inmon camp to answer some tough questions about the effectiveness of the relational approach. Cowritten by one of the best-known experts of the Inmon approach, Claudia Imhoff, this team of authors addresses head-on the challenging questions raised by Kimball in his letter and offers a how-to guide on the appropriate use of both relational and dimensional modeling in a comprehensive business intelligence environment. In addition, you'll learn the authors' take on issues such as: Which approach has been found most successful in data warehouse environments at companies spanning virtually all major industrial sectors The pros and cons of relational vs. dimensional modeling techniques so developers can decide on the best approach for their projects Why the architecture should include a data warehouse built on relational data modeling concepts The construction and utilization of keys, the historical nature of the data warehouse, hierarchies, and transactional data Technical issues needed to ensure that the data warehouse design meets appropriate performance expectations Relational modeling techniques for ensuring optimum data warehouse performance and handling changes to data over time, 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, Data warehousing is split into two camps: Ralph Kimball leads those who champion a technique called dimensional modeling; Bill Inmon leads the rest who believe in using relational modeling techniques.
LC Classification Number
QA76.9.D37

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