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QlikView: Advanced Data Visualization

You're reading from   QlikView: Advanced Data Visualization Discover deeper insights with Qlikview by building your own rich analytical applications from scratch

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Product type Course
Published in Dec 2018
Publisher Packt
ISBN-13 9781789955996
Length 786 pages
Edition 1st Edition
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Authors (4):
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Barry Harmsen Barry Harmsen
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Barry Harmsen
Miguel  Angel Garcia Miguel Angel Garcia
Author Profile Icon Miguel Angel Garcia
Miguel Angel Garcia
Stephen Redmond Stephen Redmond
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Stephen Redmond
Karl Pover Karl Pover
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Karl Pover
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Table of Contents (25) Chapters Close

QlikView: Advanced Data Visualization
Contributors
Preface
1. Performance Tuning and Scalability FREE CHAPTER 2. QlikView Data Modeling 3. Best Practices for Loading Data 4. Advanced Expressions 5. Advanced Scripting 6. What's New in QlikView 12? 7. Styling Up 8. Building Dashboards 9. Advanced Data Transformation 10. Security 11. Data Visualization Strategy 12. Sales Perspective 13. Financial Perspective 14. Marketing Perspective 15. Working Capital Perspective 16. Operations Perspective 17. Human Resources 18. Fact Sheets 19. Balanced Scorecard 20. Troubleshooting Analysis 21. Mastering Qlik Sense Data Visualization Index

Customer stratification


We had the following user story:

Note

As a sales representative, I want to see who my most important customers are so that I can focus my time and effort on them.

A customer's importance is determined by a mixture of measures. In the sales perspective, we started to determine a customer's importance using a Pareto analysis over sales. The following diagram shows the results of a customer stratification based on sales:

We can use Pareto analysis to stratify all measurements whose total is the sum of its parts, such as gross profit and quantity. However, there is another set of customer metrics whose total is an average of its parts. For example, the total company DSO is a weighted average of the DSO of each customer. In this case, we use quartiles to stratify customers.

Finally, once we have more than one measurement that stratifies customers, we look at how to combine them both numerically and visually. Even though we discuss customer stratification, the same principles...

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