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Product Description
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
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
Inside This Book
(Learn More)
First Sentence
Ideally, you must start the design of your ETL system with one of the toughest challenges: surrounding the requirements. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Ideally, you must start the design of your ETL system with one of the toughest challenges: surrounding the requirements. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
4.9 out of 5 stars (15 customer reviews)
20 of 20 people found the following review helpful
5.0 out of 5 stars
Another strong Data Warehousing book from Ralph Kimball, Nov 23 2004
By D. Mathews - Published on Amazon.com
This review is from: The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data (Paperback)
In this book Ralph lays down a framework for constructing the DW ETL. This is useful not just in constructing quality ETL processes, but also because Ralph's works tend to 'set' standards in data warehousing. The format of this book is similar to the Lifecycle Toolkit. Ralph takes a very staged, logical approach to the material. Some sections are just great e.g. the chapters on Extraction and Development. A small amount of the material is repeated from the Lifecycle Toolkit and Dimensional Modeling books, but no more than is needed to make this book stand on its own.Also like the other books, this one takes a vendor agnostic approach. While this may increase the shelf-life of the book, I would have appreciated some comparisons between the major vendors out there today.
Overall: I recommend this one as a buy, even if you have Ralph's other books.
8 of 8 people found the following review helpful
5.0 out of 5 stars
Great coverage of the ETL building blocks, Dec 18 2005
By Vincent Mcburney - Published on Amazon.com
This review is from: The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data (Paperback)
This is one of the few references out there providing the building blocks of good ETL design. There is plenty of technical documentation and forums out there that are specific to one ETL tool or DBMS but this is a better starting place for ETL developers. It is required reading as ETL projects often take short cuts in design, data quality and metadata management and reporting. This leads to very expensive Data Warehouse administration costs and often a complete rebuild of load jobs.The book is relevent for people using most ETL or ELT tools and it will remain relevent for years even as the ETL products continue to advance and mature. It is targeted at DW but the basic flow of Extract, Clean, Conform and Deliver is suitable for most types of data loads.
Good coverage of the alternatives to traditional overnight bulk loads in the section on real-time ETL systems (also describes Microbatch) as the businesses and the major ETL vendors shift to SOA.
12 of 14 people found the following review helpful
5.0 out of 5 stars
An almost complete dwh design with ETL orientation, Mar 21 2005
By Massimiliano Celaschi - Published on Amazon.com
This review is from: The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data (Paperback)
This book takes almost all issues in a data warehouse design and represents them oriented to ETL features. Actually, ETLing matches the whole of the data warehouse (more or less), so the need to describe them makes this book an autonomous work you can read without referring to previous books by Kimball. Besides, I think that some technical descriptions have been better performed here: in my experience it is impossible to undertake dwh activities without (at least) a sound knowledge about general features (indexes, use of a bulk loader vs. INSERT, etc.) of RDBMS, and this paper addresses them conveniently. On the other hand, the flat style used lacks to give evidence to the very significant issues, which happen so to be mixed up with less important statements; that demands to pay high attention while reading, but a blurring boundary between subtleties and trivialities seems to be a common shortcoming in dwh literature. Even with that flaw, the ETL Toolkit turn out as an outstanding reference to state of the art of dwh technology.
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