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The Data WarehouseETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data [Kindle Edition]

Ralph Kimball , Joe Caserta
4.0 out of 5 stars  See all reviews (4 customer reviews)

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Book 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

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Product Description

From the Back Cover

The single most authoritative guide on the most difficult phase ofbuilding a data warehouse

The extract, transform, and load (ETL) phase of the datawarehouse development life cycle is far and away the mostdifficult, time–consuming, and labor–intensive phase of building adata warehouse. Done right, companies can maximize their use ofdata storage; if not, they can end up wasting millions of dollarsstoring obsolete and rarely used data. Bestselling author RalphKimball, along with Joe Caserta, shows you how a properly designedETL system extracts the data from the source systems, enforces dataquality and consistency standards, conforms the data so thatseparate sources can be used together, and finally delivers thedata in a presentation–ready format.

Serving as a road map for planning, designing, building, andrunning the back–room of a data warehouse, this book providescomplete coverage of proven, timesaving ETL techniques. Beginningwith a quick overview of ETL fundamentals, it then looks at ETLdata structures, both relational and dimensional. The authors showhow to build useful dimensional structures, providing practicalexamples of techniques.

Along the way you’ll learn how to:

  • Plan and design your ETL system
  • Choose the appropriate architecture from the many possibleoptions
  • Build the development/test/production suite of ETLprocesses
  • 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 aleading visionary in the data warehousing industry since 1982 andis one of today s best–known speakers and educators. He isthe author of several bestselling titles published on datawarehousing, including The Data Warehouse Toolkit (Wiley).

JOE CASERTA is the founder of Caserta Concepts, LLC, a datawarehousing consulting firm. He writes frequently for print andonline magazines, and is an active contributor to DWList, the majoronline community for data warehousing professionals.


Product details

  • Format: Kindle Edition
  • File Size: 4247 KB
  • Print Length: 528 pages
  • Publisher: Wiley; 1 edition (10 Dec. 2007)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B006JAWFE4
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • : Not Enabled
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Bestsellers Rank: #164,384 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Customer Reviews

4.0 out of 5 stars
4.0 out of 5 stars
Most Helpful Customer Reviews
12 of 12 people found the following review helpful
4.0 out of 5 stars Woolly at times - but good overall 16 Jun. 2006
By John Ryan HALL OF FAME TOP 10 REVIEWER
Format:Paperback|Verified Purchase
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.
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32 of 33 people found the following review helpful
2.0 out of 5 stars Wordy, vague and few "Practical Techniques" 27 Jan. 2005
By N. Chivers VINE VOICE
Format:Paperback|Verified Purchase
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?
Read more ›
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1 of 1 people found the following review helpful
5.0 out of 5 stars Excellent Buy 3 April 2013
Format:Paperback|Verified Purchase
Fantastic down to earth explanations with real business situations.
Worth buying if you are a starter in the DW technology.
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5.0 out of 5 stars Five Stars 7 Aug. 2014
Format:Paperback|Verified Purchase
I love all Kimball's books. That one as well. He is the truth in DW/BI development :)
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Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com: 4.5 out of 5 stars  34 reviews
23 of 24 people found the following review helpful
5.0 out of 5 stars Another strong Data Warehousing book from Ralph Kimball 23 Nov. 2004
By D. Mathews - Published on Amazon.com
Format: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.
10 of 10 people found the following review helpful
5.0 out of 5 stars Great coverage of the ETL building blocks 19 Dec. 2005
By Vincent Mcburney - Published on Amazon.com
Format: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.
13 of 15 people found the following review helpful
5.0 out of 5 stars An almost complete dwh design with ETL orientation 22 Mar. 2005
By Massimiliano Celaschi - Published on Amazon.com
Format: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.
6 of 6 people found the following review helpful
5.0 out of 5 stars A handy tool on the desk of any ETL Developer. 27 Jun. 2006
By Andre Ackermann - Published on Amazon.com
Format:Paperback
I am currently working as an ETL Developer at a company

Fourier Approach, Centurion, South Africa.

Most of the time this is a fairly hot seat -

because so many business requirements are dependant on the

Quality of Information produced by the ETL process.

I always asked myself,

* Am I doing the right thing?

* Is this the best solution?

* How would other developers do this?

A while ago I attended the course

"ETL Architecture and Design Workshop"

presented by Joe Caserta, and hosted by Alicornio Africa in Johannesburg, South Africa.

Before the presentation we received a copy of the book

"The Data Warehouse ETL Toolkit".

This changed my whole perspective.

The book adressed all my ETL questions,

with examples from real-world situations.

It covers the whole ETL process and gives answers

to almost every question you will ever think of asking.

I must say this is a very handy tool on the desk of any serious ETL Developer.

Regards,

André Ackermann

ETL Developer
10 of 12 people found the following review helpful
4.0 out of 5 stars Could use more details and examples 9 Jun. 2009
By Franklin Hu - Published on Amazon.com
Format:Paperback
For a book which has "ETL Toolkit" in the name, I would think this would get right down to the nuts and bolts of how to write an ETL system. Yet, after reading this book, I still have the feeling that I still wouldn't know how to build one. From the book, I know what the issues are about inserting, deleting, and organizing the data, but how does that translate into SQL which actually does the work? There are hardly any SQL or sample code to go by. Issues like dealing with multiple database sources are mentioned, but just what do you do when cities are mentioned in both databases and they don't quite match up? If you decide to roll your own, the book really doesn't give you any basic framework to follow. This book does provide important insights on ETL systems, but don't expect to be able to write one based on this book. For example, you are told to bulk insert data, but you are also expected to exchange all of the natural keys with surrogate keys. If you have to examine each line and exchange keys, you cannot bulk load the data and this ends up being a very CPU intensive process where each row is laboriously examined, exchanged and then inserted one row at a time. This is a very practical ETL difficulty but yet, the book doesn't deal with this problem. It just assumes this won't be a problem for you. In some ways, the book is more about selling you the 'Kimbal' way of data warehouses as other more intuitive ways of constructing a data warehouse are not even considered. Like a sales pitch and a fancy powerpoint presentation, it lacks the substance to actually create a well performing ETL process. That is left as an exercise for the reader.
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