Product Description

• Cowritten by Ralph Kimball, the world′s leading data warehousing authority, whose previous books have sold more than 150,000 copies
• Delivers real–world solutions for the most time– and labor–intensive portion of data warehousing–data staging, or the extract, transform, load (ETL) process
• Delineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouse
• Offers proven time–saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality

Product Details

• Amazon Sales Rank: #87238 in Books
• Published on: 2004-09-24
• Original language: English
• Number of items: 1
• Binding: Paperback
• 528 pages

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

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.

Customer Reviews

Wordy, vague and few "Practical Techniques"
Computing is an exact and unambiguous discipline; consequently I want my computer books to be written in an exact and unambiguous manner. "The Data Warehouse ETL Toolkit" falls far short of this requirement, being wordy, vague, overblown and crammed with jargon. Worst of all, I found there were very few "Practical Techniques" I could take away with me that would help me in my work.

Here's a sample sentence: "This section discusses what needs to go into the data-cleansing baseline for the data warehouse, including simple methods for detecting, capturing and addressing common data-quality issues and procedures for providing the organisation with improved visibility into data-lineage and data-quality improvements over time". Now imagine a whole book written like this. OK, I've taken this sentence out of context, but if I tell you that this was used to introduce a section - there are no preceding or trailing sentences - then I think I am starting to paint a picture.

The authors and publishers seem to have taken the attitude, "Why use a bullet point when a paragraph will do?". Text and examples have been embellished as if in an effort to prove how clever the authors are. A lot of jargon is employed (no glossary), but the reader is always left in doubt as to whether this is industry standard or idiom employed only by the authors.

I think this book could have been so much more useful if they had taken a worked example right through from start to finish. They could have explained where the real world may be different to this perfect model and drawn on their experiences to add colour. Also, if this truly was supposed to be a book of practical techniques, they should have highlighted them, say 1 to 100, through the text, as applicable.

So why two stars rather than none? Firstly, because there are some good nuggets of information in there, if you work hard to find them, and secondly, because the authors' interest for the subject does show through. They do have a knack of answering the important questions, but only after a long journey round the houses first.

Kimball and Caserta would probably be fantastic consultants to have on a big data warehousing project, unfortunately they are awful technical writers - only buy this book if nothing else covers the subject you are interested in.

Woolly at times - but good overall
Problem with this book is it is a bit woolly and wordy (just like the previous reviewer described). However, the main difficulty is there simply is no other book around on the market. As a description of the entire end-to-end ETL process, including many subject areas I'd not even considered (eg. COBOL copy books), it's very good.

However, I'd say the REAL reason for buying this book is it works well with Ralph Kimballs other work "The Data Warehouse Toolkit", and gives an excellent summary of Dimensional Design. I guess the authors felt they must put this in to explain the background. Personally I found it invaluable.

Also the description of "real time ETL" was invaluable. Everyone's talking about it, but the book gives a credible outline solution.

Yes woolly, yes it uses 10 words when two would do, but overall I got a lot out of it.

Recommended.