Practical Data Quality: Learn practical, real-world strategies to transform the quality of data in your organization


Practical Data Quality: Learn practical, real-world strategies to transform the quality of data in your organization
by: Robert Hawker (Author), Nicola Askham (Foreword)
Publisher finelybook 出版社: ‎Packt Publishing (September 29, 2023)
Language 语言: ‎English
Print Length 页数: ‎318 pages
ISBN-10: ‎180461078X
ISBN-13: ‎9781804610787


Book Description
By finelybook

Identify data quality issues, leverage real-world examples and templates to drive change, and unlock the benefits of improved data in processes and decision-making
Key Features
Get a practical explanation of data quality concepts and the imperative for change when data is poor
Gain insights into linking business objectives and data to drive the right data quality priorities
Explore the data quality lifecycle and accelerate improvement with the help of real-world examples
Purchase of the print or Kindle book includes a free PDF eBook

Book Description
By finelybook

Poor data quality can lead to increased costs, hinder revenue growth, compromise decision-making, and introduce risk into organizations. This leads to employees, customers, and suppliers finding every interaction with the organization frustrating.
Practical Data Quality provides a comprehensive view of managing data quality within your organization, covering everything from business cases through to embedding improvements that you make to the organization permanently. Each chapter explains a key element of data quality management, from linking strategy and data together to profiling and designing business rules which reveal bad data. The book outlines a suite of tried-and-tested reports that highlight bad data and allow you to develop a plan to make corrections. Throughout the book, you’ll work with real-world examples and utilize re-usable templates to accelerate your initiatives.
By the end of this book, you’ll have gained a clear understanding of every stage of a data quality initiative and be able to drive tangible results for your organization at pace.
What you will learn
Explore data quality and see how it fits within a data management programme
Differentiate your organization from its peers through data quality improvement
Create a business case and get support for your data quality initiative
Find out how business strategy can be linked to processes, analytics, and data to derive only the most important data quality rules
Monitor data through engaging, business-friendly data quality dashboards
Integrate data quality into everyday business activities to help achieve goals
Avoid common mistakes when implementing data quality practices
Who this book is for
This book is for data analysts, data engineers, and chief data officers looking to understand data quality practices and their implementation in their organization. This book will also be helpful for business leaders who see data adversely affecting their success and data teams that want to optimize their data quality approach. No prior knowledge of data quality basics is required.

Table of Contents
1. The Impact of Data Quality on Organizations
2. The Basics of Data Quality
3. The Business Case for Data Quality
4. Data Quality Roles and Their Challenges
5. Data Discovery
6. Data Quality Rules
7. [Monit oring Dat a Ag ainst Rules
8. Data Quality Remecdiation
9. Embedding Data Quality into Organizations
1o. Best Practices and Common Ivlistakes
Review
“There are several complex concepts that you need to get your head around when working on a data quality initiative and I admire the way that Rob uses his extensive experience in the field to explain these in a simple, accessible way, providing excellent examples and use cases, along with examples of frequently made mistakes to bring it all to life.”

Nicola Askham, The Data Governance Coach
About the Author
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. Amazon page

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