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Practical Data Quality

You're reading from Practical Data Quality

Product type Book

Published in Sep 2023

Publisher Packt

ISBN-13 9781804610787

Pages 318 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Author (1):

Robert Hawker

Table of Contents (16) Chapters

Preface

1. Part 1 – Getting Started

2. Chapter 1: The Impact of Data Quality on Organizations

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

Why subscribe?

15. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

architectural review board (ARB) 238

artificial intelligence (AI)-driven large language models (LLMs) 277

Attacama DQ Analyzer tool

reference link 143

Azure Active Directory group 156

B

bad data

detailed definition 5, 6

versus perfect data 6, 7

bad data, causes 16

lack, of data culture 16

merger and acquisition scenarios 18

process speed, prioritizing over data governance 16, 17

bad data quality, impact 7

analytics impact 12, 13

compliance impacts 13-15

data differentiation impacts 15

efficiency impact 9-11

process impact 9-11

qualitative 9

quantification 8, 9

reporting impact 12, 13

best practices 257, 270, 271

data quality, including in organization-wide education program 264, 265

data quality, managing at source 258-260...

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Authors (1)

Robert Hawker

Robert Hawker started his career as a chartered accountant before making the leap into data in 2007. He led data teams within two global implementations of SAP, looking after master data management, data ownership and stewardship, metadata management, and, of course, data quality over a 14-year period. He moved into analytics in 2017 and now specializes in Microsoft Power BI training, implementation, administration, and governance work. He lives in the UK and shares his experiences through conference and blogs.

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