- Paperback: 464 pages
- Publisher: Wiley; 2 edition (April 26, 2002)
- Language: English
- ISBN-10: 0471200247
- ISBN-13: 978-0471200246
- Product Dimensions: 7.4 x 1 x 9.2 inches
- Shipping Weight: 1.5 pounds
- Average Customer Review: 65 customer reviews
- Amazon Best Sellers Rank: #197,384 in Books (See Top 100 in Books)
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The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling 2nd Edition
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"...this is the daddy of data warehousing process books. No other material available so concisely and precisely explains what is required from a data warehousing solution...this is a great book..." (Enterprise Server Magazine, July 2002)
From the Back Cover
The latest edition of the single most authoritative guide on dimensional modeling for data warehousing!
Dimensional modeling has become the most widely accepted approach for data warehouse design. Here is a complete library of dimensional modeling techniques-- the most comprehensive collection ever written. Greatly expanded to cover both basic and advanced techniques for optimizing data warehouse design, this second edition to Ralph Kimball's classic guide is more than sixty percent updated.
The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including:
* Retail sales and e-commerce
* Inventory management
* Order management
* Customer relationship management (CRM)
* Human resources management
* Financial services
* Telecommunications and utilities
* Health care and insurance
By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.
Wiley Computer Publishing. Timely. Practical. Reliable.
Visit our Web site at www.wiley.com/compbooks/
Visit Kimball's Web site at www.kimballuniversity.com
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Kimball's concept is founded on the notion of a "dimensional model" for database. Quite interestingly, Kimball pleads ignorance relative to the question of the actual origins of this dimensional approach. With this, I can be of assistance. In the early days of the Decision Support Software industry, there was a product known as Express. I believe the vendor was Management Decision Sciences, Inc., or something like that. This product competed, at one level, with IFPS, the Integrated Financial Planning System(IFPS), which was sort of like fancy Fortran, and at another level with the then emerging world of relational database software. I still remember meetings from back in the early 80's when proponents of Express would argue passionately that data ought to be organized in "cubes", the forerunner, and predecessor, Ralph, of dimensions. Now, when you pinned the technical folks advocating such an approach down, they would finally admit that what they were talking about was really nothing more than a fancy array processor. That's what it was. And that is the essence of this whole "dimensional model" concept.
It is interesting to compare and to contrast the approaches taken by Inmon and Kimball in their respective books on Data Warehousing. Inmon acknowledges that there is a debate extant. He also respectfully cites Kimball's contributions to the debate within the corpus of his text. Kimball is silent on the identity of his rival. And this silence really speaks volumes. He, Kimball, that is, is also strangely silent on even the efficacy of a relational design of any warehouse data structure, finally allowing that you may allow such a thing in a "staging area". But you mustn't let your users know about it. This is the strangest sort of censorship of important corporate data I've ever encountered. Consider the following: Suppose we work for an organization with say, seven million customers. Should we not, in this instance, have a relational database table somewhere that has seven million rows, one row representing each customer? And should not this table be readily available to our user community? These questions are intended to be rhetorical. However, on reading Kimball's book, we judge that he, and his followers, would strongly resist such a common sense line of reasoning.
Kimball's book is noteworthy in so far as he does present many interesting, and potentially useful, designs. However, his mute avoidance of the essence of the ongoing debate says all we really need to know about his outreach. Were the good Dr. Codd, inventor of the Relational Model for Database, alive today, it seems clear that he would give Ralph Kimball a good scolding, and direct him to stick to end user analysis, leaving actual issues of database design to more fully arrived professionals.
A couple of pages later, on page 18, I see this passage. "The fact table itself generally has its own primary key made up of a subset of the foreign keys. This key is often called a composite or concatenated key. Every fact table in a dimensional model has a composite key, and conversely, every table that has a composite key is a fact table. Another way to say this is that in a dimensional model, every table that expresses a many-to-many relationship must be a fact table". I am confused, for three reasons. A fact table's primary key is "generally" made up of a subset of foreign keys? This is not the case with Kimball's own first fact table on page 36 - "POS Transaction Number" definitely should be part of a primary key (he does not define one, so I assume), but it does not foreign-key into anything. Oh, and Sentence 3 means it's "always", not "generally", if we follow the "conversely" path. Is the "another way to say this" part true? ... And overall, isn't this all just a confused way to say that fact tables have foreign keys and dimension tables don't? "Stars, no snowflakes". (What's wrong with snowflakes, apart from the increased design complexity? Among the reasons listed on page 60 - views are never mentioned - the technical and the scariest one is "snowflaking defeats the use of bitmap indexes").
The two examples above are representative of the book's style, and I am quite sure that it could use a lot more editing. I wish that somebody did a better job, but don't know a reasonable substitute. (Yes, I have seen Inmon's book - not a fan). Nonetheless, it's an impressive, concrete book that will give you a lot of practical ideas, and, when it suggests something that looks suboptimal or incomplete or self-contradictory, will make you think about schema design. Not a sufficient reference on the subject, but a very necessary one.
PS. I recommend "Kimball Group Reader" as the alternative to this book: I believe that it covers the material here, and offers a lot of additional information.
very bad organization, not clear but confusing sometimes, and very poor logical flow... he tries to make a big deal out of DW, when in fact it's not such a fancy or intellect intensive subject. very simple concepts are even hard to understand. someone else would be able to write a book more powerful and straight to the point in 100 pages MAX, and be much more useful....
it sucks when leaders don't know how to express themselves, maybe he was looking forward to have readers learn enough in DW to get projects started but not be able to do squat, and get some business from consulting...