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Mastering QlikView

You're reading from   Mastering QlikView Let QlikView help you uncover game-changing BI data insights with this advanced QlikView guide, designed for a world that demands better Business Intelligence

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Product type Paperback
Published in Nov 2014
Publisher
ISBN-13 9781782173298
Length 422 pages
Edition 1st Edition
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Author (1):
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Stephen Redmond Stephen Redmond
Author Profile Icon Stephen Redmond
Stephen Redmond
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Table of Contents (9) Chapters Close

Preface 1. Performance Tuning and Scalability FREE CHAPTER 2. QlikView Data Modeling 3. Best Practices for Loading Data 4. Data Governance 5. Advanced Expressions 6. Advanced Scripting 7. Visualizing Data Index

Dimensional data modeling

There are several methodologies for implementing a data warehouse or data mart that might be useful to consider when implementing QlikView in an organization. However, for me, the best approach is dimensional modeling—often called Kimball dimensional modeling—as proposed by Ralph Kimball and Margy Ross in the book The Data Warehouse Toolkit, John Wiley & Sons, now available in its third edition.

Some other methodologies, most noticeably that proposed by Bill Inmon, offer a "top-down" approach to data warehousing whereby a normalized data model is built that spans the entire enterprise, then data marts are built off this to support lines of business or specific business processes. Now, QlikView can sit very readily in this model as the data mart tool, feeding off the Enterprise Data Warehouse (EDW). However, QlikView cannot implement the normalized EDW.

In my opinion, Kimball dimensional modeling, on the other hand, is right up QlikView...

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