Product Description
Designing complex analytical data structures is difficult enough, but to do it for an entire enterprise becomes a real challenge. This little primer provides a simple method of preparing your people for the complexity of this endeavor. This is just like opening a new restaurant where certain components have to be designed and thought out before you start to build the kitchen. You do not have to be an “expert” to build a data warehouse. A lot can be outsourced, but y… More >>
Implementing Enterprise Data Warehousing: A Guide for Executives
Implementing Enterprise Data Warehousing is to the point, clear, and an important tool for managers to enhance their understanding of this field. The glossary alone is worth the book to understand the language of this area. I see this as a resource to help managers make good decisions with reduced losses in the area of Data Warehousing. I recommend this for anyone who wants their data to work for them vs. enslaving them. – ¬Martin Brossman, CRSP-T Executive & Sales Coach
Rating: 5 / 5
Implementing Enterprise Data Warehousing by Alan Schlukbier (Lulu.com, 2007) is the world’s first meta book. (No, a meta book is not a book about metadata. Read on.)
The subject of enterprise data warehousing is a large and intimidating subject, and there are volumes of books and articles written about it. To read everything on the subject is a large task, to say the least. And most executives just don’t have time to become an expert in this complex field.
Accordingly, Alan Schlukbier has approached the enterprise data warehousings from the standpoint that executives have a lot on their minds and that they don’t have the time or motivation to read everything that they need to know about building and implementing enterprise data warehouses. He has written an imminently readable book that covers the subject at an executive level. It is an executive summary for all of the other works that exist on enterprise data warehousing.
As such, the book is short (which is one of its virtues). It is not intimidating, which is another of its virtues. An executive truly can pick it up, read it and learn the larger framework that the executive needs to know.
The book does not pretend to be the last word on enterprise data warehousing (EDW) implementation. Instead, it is positioned as the first word.
In case after case, Schlukbier points the reader to other works in the industry. This is why it is a meta book.
The book is complete in that it introduces the reader to the many different aspects of EDW development and implementation. Some of the topics that are covered include:
* Data quality
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* Data stewardship
* Data modeling
* Data governance
* ETL
* Data mining
* Master data management (MDM)
The aim of this book is breadth, not depth. And maybe on occasion this is exactly what executives need.
A final thought is that the book is peppered with anecdotes. These pithy anecdotes drive home the central themes of discussion and lend an air of realism to the book.
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* Bill InmonBill Inmon
Bill is universally recognized as the father of the data warehouse. He has more than 36 years of database technology management experience and data warehouse design expertise. He has published more than 40 books and 1,000 articles on data warehousing and data management, and his books have been translated into nine languages. He is known globally for his data warehouse development seminars and has been a keynote speaker for many major computing associations. Bill can be reached at 303-681-6772.
Editor’s note: More articles, resources, news and events are available in Bill’s BeyeNETWORK Expert Channel. Be sure to visit today!
Rating: 5 / 5
The idea of a simple, short guide that could be used to prepare senior managers for a journey into EDW is a great idea.
The problem is, this book is so poorly written and edited, it distracts from the concepts being conveyed. You can find an error in grammar every few pages. Even the choice of font in the book (Times Roman) makes it look unprofessional and outdated.
Nuggets of information are sometimes offered with no explanation, so they don’t seem rational. “An ideal data modeling team is about 3 [people] with a strong manager.” Is that true for every company of every size? Why?
Or terms are introduced with no background, that might be inappropriate for senior business managers. The first paragraph in chapter 1 references 3NF databases without explaining what that means. The comment itself would just distract the target audience.
This book was recently recommended by Bill Inmon in his newsletter, and I bought it on that recommendation. I’m disappointed.
Rating: 1 / 5
I think there are some good ideas behind this book, but I don’t think that the actual content conveys those ideas very clearly or effectively.
The first dozen pages are definitely worth reading. Alan makes a valuable point about architecture: one key goal of enterprise-scale architecture is to simplify and reduce redundancy. He draws an analogy to data modeling normalization techniques, which I think it a very good comparison.
Hidden in the first main section of the book, Alan does make some very good points about data and system governance. The rest is of the book, however, I felt was incoherent. The book could have benefited greatly from an editor to help refine the message, the flow, and the style.
I would have expected there to be a big section on making the business case for enterprise data warehousing, data governance, data stewardship, and master data management, but I got neither that nor any practical advice on how to push those initiatives forward within an established organization.
It’ll sit on my shelf with a “not worth reading” recommendation on it.
Rating: 1 / 5