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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
Author Profile Icon Barry Harmsen
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
Author Profile Icon Karl Pover
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

Data teams and roles


The exact composition of the teams whose principal job is to enable their coworkers to make data-driven decisions will vary as a business's entire data strategy matures. However, many misinterpret what it means to run a mature data-driven business. They believe that at some point all data will and should be governed, and that the team that develops the first QlikView data exploration and discovery projects with will be that governing body.

While a mature data-driven business does count with a large set of governed data and a talented data governance team, it should never be without new, unknown datasets, or without ideas about how to exploit existing datasets in new ways. It is also unrealistic that the same team enforce conformity at the same time that they must strive to innovate. It is for that reason that every mature data-driven business should have both a data research and development (R&D) team, and a data governance team. Each team will have a different data...

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