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Practical Data Quality

You're reading from   Practical Data Quality Learn practical, real-world strategies to transform the quality of data in your organization

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781804610787
Length 318 pages
Edition 1st Edition
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Author (1):
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Robert Hawker Robert Hawker
Author Profile Icon Robert Hawker
Robert Hawker
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Table of Contents (16) Chapters Close

Preface 1. Part 1 – Getting Started
2. Chapter 1: The Impact of Data Quality on Organizations FREE CHAPTER 3. Chapter 2: The Principles of Data Quality 4. Chapter 3: The Business Case for Data Quality 5. Chapter 4: Getting Started with a Data Quality Initiative 6. Part 2 – Understanding and Monitoring the Data That Matters
7. Chapter 5: Data Discovery 8. Chapter 6: Data Quality Rules 9. Chapter 7: Monitoring Data Against Rules 10. Part 3 – Improving Data Quality for the Long Term
11. Chapter 8: Data Quality Remediation 12. Chapter 9: Embedding Data Quality in Organizations 13. Chapter 10: Best Practices and Common Mistakes 14. Index 15. Other Books You May Enjoy

Designing a high-level data quality dashboard

Every data quality initiative is different, and senior stakeholders at different organizations will have different needs. The example developed for this book is an amalgamation of various concepts successfully applied at different organizations. The figures in this section can be used as a starting point for discussions, but it is critical to get stakeholders involved in the design process.

This section explains the typical design of the various Data Quality Dashboards and reports. It should be possible to apply organizational differences to this typical approach to make it work for your organization.

Dimensions and filters

The high-level Data Quality Dashboard for the senior stakeholder is typically a simple data visualization aimed at showing a data quality summary for the following displayed dimensions:

  • Each process area
  • Each data object
  • Each business unit
  • Each region

The report is typically kept simple...

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