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The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data
Ebook Download The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data
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From the Back Cover
The single most authoritative guide on the most difficult phase of building a data warehouse The extract, transform, and load (ETL) phase of the data warehouse development life cycle is far and away the most difficult, time-consuming, and labor-intensive phase of building a data warehouse. Done right, companies can maximize their use of data storage; if not, they can end up wasting millions of dollars storing obsolete and rarely used data. Bestselling author Ralph Kimball, along with Joe Caserta, shows you how a properly designed ETL system extracts the data from the source systems, enforces data quality and consistency standards, conforms the data so that separate sources can be used together, and finally delivers the data in a presentation-ready format. Serving as a road map for planning, designing, building, and running the back-room of a data warehouse, this book provides complete coverage of proven, timesaving ETL techniques. Beginning with a quick overview of ETL fundamentals, it then looks at ETL data structures, both relational and dimensional. The authors show how to build useful dimensional structures, providing practical examples of techniques. Along the way you'll learn how to: Plan and design your ETL system Choose the appropriate architecture from the many possible options Build the development/test/production suite of ETL processes Build a comprehensive data cleaning subsystem Tune the overall ETL process for optimum performance
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About the Author
RALPH KIMBALL, PhD, founder of the Kimball Group, has been a leading visionary in the data warehousing industry since 1982 and is one of today's best-known speakers and educators. He is the author of several bestselling titles published on data warehousing, including The Data Warehouse Toolkit (Wiley). JOE CASERTA is the founder of Caserta Concepts, LLC, a data warehousing consulting firm. He writes frequently for print and online magazines, and is an active contributor to DWList, the major online community for data warehousing professionals.
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Product details
Paperback: 528 pages
Publisher: Wiley; 1 edition (October 1, 2004)
Language: English
ISBN-10: 8126505540
ISBN-13: 978-0764567575
ASIN: 0764567578
Product Dimensions:
7.3 x 1 x 9.2 inches
Shipping Weight: 1.7 pounds (View shipping rates and policies)
Average Customer Review:
4.4 out of 5 stars
39 customer reviews
Amazon Best Sellers Rank:
#125,644 in Books (See Top 100 in Books)
There's a lot of info here and it amounts to a college text. It's very in depth and will require as much time as any college text would. Several chapters stand out like Cleaning and Conforming. Metrics development is discussed in depth in ways that may have been overlooked in other texts like this one. The examples go very deep into generation of surrogate keys, bulk loading of Type 1s, minimum key requirements in dimensions and other ETL concepts concerning the error audit table. The book was written very obviously from practical situations encountered in daily work.The book does not present or attempt to develop the "Kimball Method" of SCD. As it turns out, that's far less important than all the other things required simply to do a day's ETL cycle for which much may go wrong. Numerous tips are worked into this text. It seems that the small things add up greatly throughout a review of the book. For example, it's a mistake to allow NULLs ever to be the prime indicator for an active Type 2 record specifically because a simple SQL call needing a date range controlled by BETWEEN will fail if the active indicator is NULL. It's the fine points like this that rate this book very highly.This is not a trivial one-time-only to read book. It seems that this sort of preparation should be more in evidence in many of the shops. Let's face it. IT but especially ETL is a high end engineering discipline, more so with EDW.As far as criticisms are concerned, the SQL examples are good but are PL/SQL and require time to decode for those developing in MSSQL environments. The book was written in 2002 when Oracle was the main player and there were not so many Teradata shops. That may make the book too back level for some readers. However, the book covers most of the subject matter devoid of specific implementation specifics, enough so that the key concepts would work regardless of the technology chosen.It's not very likely that a course like this one would even be taught at a college level and for that reason the book is a key investment. Further, this book could be used for two full semesters, based on this reviewer's experience in formal course work. It's not likely that on-the-job training would supplant the need for the knowledge contained in this book or one like it.
This is a good book to read if you want to put yourself to sleep. The writing is rather dry and important concepts are not clearly and easily explained. There's a reason why they say to reread one of the chapters, it is just not easily comprehensible. By providing more data examples, this book would go a long way in explaining some of the more difficult to comprehend concepts. Also, since some of the words are defined and reused throughout the book, it would have been great if the definitions would be better.Given that this book was written more than 10 years ago, many things have changed and an update is desparately needed.
Great book, I found it very helpful as I started in a new role developing data warehouses and ETL processes. The only downside is that the book was misprinted. I purchased this through TextbookRush and chapter 6 of this book was missing and instead pages from Sex For Dummies was included.
This seems to be a good book but I would not suggest getting the kindle version as I am not able to view the diagrams on my kindle they are way too small and cannot be resized. You miss key information from not being able to view the diagrams. Apart from this I would recommend the book, just not the kindle version. I have the Black and white Kindle, not the new Kindle Fire. Not sure if that makes a difference.
I've been doing this for 9 years, and this is the best book I've seen on ETL procesing and its role in data warehousing. Before you start your data warehouse effort have your team read this book. Not just the ETL members...both the front/back room technicians will benefit from understanding the clear presentation of what can be in scope (dare I say, "best practice" yikes!) for ETL processing. The ideas for capturing highly valuable data quality and cleansing processes is no less helpful than the emphasis on loading the data unless it is misleading enmasse or so obviously flawed. The bias toward driving the data to the front room for presentation forces data quality issues to the surface where they must be dealt with and the loop to operational systems (or perhaps even flawed ETL transforms!) closed. Illustrates alternatives for dealing with the messy reality of suspended data, late arriving facts and dimensions. Use it as a guide for your ETL efforts. Buy this book, read it and then buy a few more for your team if you agree.
In my estimation The Data Warehouse ETL Toolkit is a good source of information for the topic that covers the majority of your Data Warehouse efforts, the ETL process (or ECCD if you prefer, which you probably will after finishing this volume). I took away some good ideas on items that I probably would not have considered, mostly due to my own ignorance, relating to Meta Data, QA and Error Corrections, Data Lineage and Scoring, etc.The Authors (Kimball and Caserta) do a good job of pointing out other source books for items that the user will probably want to look at in depth.There is also a pretty good section explaining how to manage your ETL project, the different roles of people who should be involved and a pretty good project plan / checklist to use as you are getting started.My only complaint is that I did not read this prior to starting my own project and am instead having to correct items as I try to implement these best practices.
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