Data Mapping for Data Warehouse Design
By Qamar Shahbaz
Publisher: Elsevier / Morgan Kaufmann
Final Release Date: December 2015
Pages: 180

Data mapping in a data warehouse is the process of creating a link between two distinct data models’ (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle.

  • Covers all stages of data warehousing and the role of data mapping in each
  • Includes a data mapping strategy and techniques that can be applied to many situations
  • Based on the author’s years of real-world experience designing solutions
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By Paul

from Dublin



    • Not comprehensive enough

    Best Uses

      Comments about oreilly Data Mapping for Data Warehouse Design:

      Pretty poor detail for the money. I have had interns who have presented better more insights than this and the subjects have been covered better in any number of other books.

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