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The Data Warehouse ETL Toolkit by Ralph Kimball

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The Data Warehouse ETL Toolkit

Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data

Ralph Kimball, Joe Caserta

Wiley · Print & ebook · October 4, 2004

Reading lane: Data Warehousing

- 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

At a Glance

Who It's For

Useful to readers working on data warehouse ETL and data quality.

Book Details

Authors
Ralph Kimball, Joe Caserta
Publisher
Wiley
Published
October 4, 2004
Format
Print & ebook
Theme
Data Warehousing · Data Mining
Reading lane
Data Warehousing

Affinity

Publisher Categories

  • Data Warehousing

About This Book

- 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,...

Read full 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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