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Mastering QlikView

By : Stephen Redmond

4.5 (10)

Mastering QlikView

4.5 (10)

By: Stephen Redmond

Overview of this book

If you are a business application developer or a system analyst who has learned QlikView and Qlik Sense and now want to take your learning to a higher level, then this book is for you. It is assumed that you are aware of the fundamentals of QlikView and have working knowledge of development and in-memory analytics.

Preface

Preface

Qlik Sense

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Free Chapter

1. Performance Tuning and Scalability

1. Performance Tuning and Scalability

Reviewing basic performance tuning techniques

Generating test data

Understanding how QlikView stores its data

Strategies to reduce the data size and improve performance

Testing chart performance for different load options

Optimizing chart calculation times

The QlikView calculation engine

Using Direct Discovery

Testing scalability with JMeter

Running an example execution

Summary

2. QlikView Data Modeling

2. QlikView Data Modeling

Reviewing basic data modeling

Dimensional data modeling

Handling slowly changing dimensions

Dealing with multiple fact tables in one model

Drilling across with document chaining

Summary

3. Best Practices for Loading Data

3. Best Practices for Loading Data

Reviewing data loading concepts

Understanding why you should use an ETL approach

Using an ETL approach to create QVD data layers

Mastering loading techniques

Using QlikView Expressor for ETL

Summary

4. Data Governance

4. Data Governance

Reviewing basic concepts of data governance

Establishing descriptive metadata

Extracting metadata

Deploying the QlikView Governance Dashboard

Summary

5. Advanced Expressions

5. Advanced Expressions

Reviewing basic concepts

Understanding Dollar-sign Expansion

Using advanced Set Analysis

Calculating vertically

Summary

6. Advanced Scripting

6. Advanced Scripting

Reviewing the basic concepts

Counting records

Loading data quickly

Applying variables and the Dollar-sign Expansion in the script

Using control structures

Examining advanced Table File Wizard options

Looking at data from different directions

Reusing code

Summary

7. Visualizing Data

7. Visualizing Data

Reviewing the history of data visualization

Understanding the audience

Designing effective visualizations

Summary

Index

Index

Customer Reviews

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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:

Extract the data from data sources into QVDs.
Transform the data from the initial QVDs into transformed fact tables and conformed dimensions.
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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