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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

Using an ETL approach to create QVD data layers

We now know that there are very good reasons for adopting an ETL approach to loading data in QlikView. Now we need to learn how we should go about implementing the approach.

Each part—Extract, Transform, and Load—has its own set of recommendations because each part has a very different function.

Essentially, the approach looks like this:

Using an ETL approach to create QVD data layers

The approach can be explained as follows:

  1. Extract the data from data sources into QVDs.
  2. Transform the data from the initial QVDs into transformed fact tables and conformed dimensions.
  3. Load the transformed QVDs into the final applications.

The final two layers, the transformed QVDs and the final applications, become potential sources for a user's self-service. We can have confidence that users who load data from these layers will be getting access to clean, governed data.

Creating a StoreAndDrop subroutine

When we are loading data to create QVDs, we will end up calling the Store statement quite frequently...

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