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Goodreads helps you keep track of books you want to read. Want to Read saving…. Want to Read Currently Reading Read. Other editions. Enlarge cover. Error rating book. Refresh and try again. Open Preview See a Problem? Details if other :. Thanks for telling us about the problem. Return to Book Page. Joe Caserta. Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than , 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 redun Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than , copies.
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. Get A Copy. Paperback , pages. More Details Original Title. Other Editions 6. Friend Reviews. To see what your friends thought of this book, please sign up.
Lists with This Book. Community Reviews. Showing Average rating 4. Rating details. More filters. Sort order. Jan 06, Ahmet Fuat rated it really liked it. It has many great explanations to develop an etl system to build up a dimensional model. But I think if it includes to build up an Etl project from scratch it would be really better. Nov 02, Amy Shape rated it it was amazing.
Had some helpful information on ETL practices. May 08, Moutasem Awa rated it liked it. Amazing content with great details. Shelves: bi , dwh , etl. This risk can be mitigated with the data-profiling techniques discussed in Chapter 4.
This means that security for end users is not controlled with grants and revokes to individual users at the physical table level but is controlled through roles defined and enforced on an LDAP-based network resource called a directory server.
It is then incumbent on the end users' applications to sort out what the authenticated role of a requesting end user is and whether that role permits the end user to view the particular screen being requested. This view of security is spelled out in detail in Data Warehouse Lifecycle Toolkit. In other words, in most cases the back room and front room are on different machines, depend on different data structures, and are managed by different IT personnel.
Read that sentence again! Our approach to data warehousing assumes that data access is prohibited in the back room, and therefore the front room is dedicated to just this one purpose. There are no service-level agreements for data access or consistency in the staging area.
All of these data access requirements are handled in the presentation area. If manual tables must be maintained, an application should be developed outside of the data-staging area, and the resulting data should be provided to the ETL team and incorporated into the staging area via an ETL process. Staging-area de-signs must do both. The view that data marts consist only of aggregated data is one of the most fundamental mistakes a data warehouse designer can make.
Aggregated data in the absence of the lowest-level atomic data presupposes the business question and makes drilling down impossible.
We will see that a data mart should consist of a continuous pyramid of identically structured dimensional tables, always beginning with the atomic data as the foundation" "The mission of the data warehouse is to publish the organization's data assets to most effectively support decision making.
The key word in this mission statement is publish. Just as the success of a conventional publica-tion like a magazine begins and ends with its readers, the success of a data warehouse begins and ends with its end users. Many utility programs are dedicated to text-file manipulation. Nov 14, Blessy J rated it really liked it. This is one of the best written books in a literary sense for IT, which is why I wanted to 4-star and review it on Goodreads.
I thoroughly enjoyed reading this book for its clarity, good use of language and eloquence. And what more, learnt a great deal more about Data warehousing : I recommend it to anyone who has even the slightest of inclination towards databases, data modelling and data analysis. This book is a great value addition. The book gives you an eagle's eye view of the kind of data This is one of the best written books in a literary sense for IT, which is why I wanted to 4-star and review it on Goodreads.
The book gives you an eagle's eye view of the kind of data different major industries deal with and hence the industry-specific challenges in datawarehousing them and tips and useful hacks on how to tackle these challenges so that you come back to the data in your own business with a "refreshed perspective".
Jun 15, Colin Hoad rated it it was amazing Shelves: technology-books. This is an excellent book for anyone working in data warehousing and ETL. It solidified a lot of the knowledge that I've gradually picked up over the last ten years and further improved my grasp of theory and practice.
There are some superb insights here, as well as plenty of detailed "how to" information. Not only that, but the book helps to cement how a proper, fully-fledged data warehouse project should be carried out and places the ETL function right at the heart of that endeavour. Kimball's This is an excellent book for anyone working in data warehousing and ETL.
Kimball's writing style is surprisingly approachable and readable, given the often dry subject matter. It's also impressive that, nearly 10 years on from the first edition, this book remains the definitive word on ETL. Jan 30, Naveed Sadiq added it. Jan 23, Louis Marier rated it it was amazing. The ETL reference book for developing data warehouses, whatever the technology you use.
Ranga B rated it really liked it Nov 20, Paul rated it it was amazing Jan 13, Frank O'connor rated it it was amazing Feb 27, Leigh Morgan rated it really liked it Feb 26, Karen Shortridge rated it really liked it Aug 05, Rongrongchen rated it it was amazing Aug 30, Kris rated it liked it Jun 24, Siva rated it it was amazing Dec 22, Chris rated it liked it Jan 12, Ali Khan rated it really liked it Mar 31, Alexander rated it it was amazing Feb 20, Rebecca Fernandez rated it it was amazing Aug 03, Mehul Shah rated it really liked it Dec 26, Franky rated it it was amazing Nov 02, Umar rated it really liked it Sep 23, Jgc rated it it was amazing Aug 21, Raghvendra rated it really liked it Dec 10, Julio C Ramos rated it really liked it Jun 19, Oliver Steele rated it liked it Aug 25, Manfred rated it really liked it Aug 26, Ankur rated it really liked it Sep 14, There are no discussion topics on this book yet.
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The Data Warehouse ETL Toolkit
You are currently using the site but have requested a page in the site. Would you like to change to the site? Ralph Kimball , Joe Caserta. He is the author of several bestselling titles published on data warehousing, including The Data Warehouse Toolkit Wiley.