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Practical Data Quality
Practical Data Quality

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

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Practical Data Quality

The Impact of Data Quality on Organizations

Data quality is often one of the most neglected topics in organizations. It becomes part of the culture of the organization to make statements such as The data for that report comes from our CRM system – but be warned: the data quality isn’t great or Sorry, I can’t answer that question because our data just isn’t good enough to support it. How often do you hear these statements repeated month after month – and even year after year?

When data quality is neglected in this way, it impacts the following:

  • The effectiveness of business and compliance processes
  • The ability to make high-quality decisions from reporting
  • The ability to differentiate your organization from the competition
  • The reputation of the organization with customers, suppliers, and employees

Organizations cannot leverage new technologies, such as AI and ML, to get the most out of their data. Those lofty ambitions to monetize data as a product all too often must be shelved.

Poor data quality is also an invisible drain on productivity. Every employee in an organization is impacted by poor data quality in some way – whether it is a report that doesn’t include all the information they need or a business process that they can’t complete because key data is missing. Eventually, people stop reporting the issues and create new (often highly complex) processes to deliver the required outcome despite the data quality problems. The problem of data quality is often considered to be too complex and too costly to resolve – leading to people searching for ways around the problems.

Take the example of a manufacturing organization with a highly automated product master data creation process. The products needed to be extended to the various manufacturing plants and sales organizations. This was done using tables containing rules (for example, field X should contain value Y for Italy and value Z for Germany). The process of creating products took just seconds but the underlying tables of rules had not been kept up to date, so this systematically created incorrect data for three products in one country. The incorrect data was carried over into sales invoices that reached customers. The product master data had a flag that, if ticked, meant an additional charge needed to be made for packaging. This flag was incorrectly left blank for the three products. A total of more than ten thousand invoices were distributed in six weeks without the additional packaging fee. A small issue had a substantial impact!

After reporting the product data issue consistently for many weeks – with no action taken to resolve the issue – the sales team established a process to manually correct each invoice before it reached the customer. This work was so repetitive that employee attrition became an issue. This was one of a raft of similar issues within this organization that was invisibly draining away its potential.

Does this sound like a familiar story in your organization? If so, I hope that this book helps you find a path forward.

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Key benefits

  • 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

Description

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.

Who is this book 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.

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
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 29, 2023
Length: 318 pages
Edition : 1st
Language : English
ISBN-13 : 9781804610787
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Product Details

Publication date : Sep 29, 2023
Length: 318 pages
Edition : 1st
Language : English
ISBN-13 : 9781804610787
Category :

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Table of Contents

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

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9
(13 Ratings)
5 star 92.3%
4 star 7.7%
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Jay from IL Oct 31, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Practical Data Quality, is a must read for data professionals. Robert shares his years of experience in this well packaged publication. Each section is well thought out and prefaces the larger picture of end-to-end organizational data governance and democratization. This book will stay front and center in my bookcase as a "go-to" reference.
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Zero Gravitas Oct 17, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is an excellent read, pulling all the relevant concepts together in a way that makes it really easy to think about how it would actually work in the reader’s organisation. We've already started to use it at work, as part of our overall data governance programme.
Amazon Verified review Amazon
Uygar Yörük Dec 02, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have enjoyed reading it; the book delivers on what the title promises, providing at least one real-life example for every concept mentioned. The book addresses many of the questions I have encountered regarding Data Quality initiatives throughout my consulting career. It is nicely structured, following the typical life cycle of a data quality initiative in an enterprise. This allows you to use the book as a reference, no matter which phase of your initiative you encounter a challenge.
Amazon Verified review Amazon
Will Dec 03, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
"Practical Data Quality" is a game-changer for anyone seeking a comprehensive guide to navigate the intricacies of managing data quality. The book adeptly explores the far-reaching consequences of poor data, demonstrating how it can escalate costs, hinder revenue growth, and jeopardize decision-making. With a strategic approach, it seamlessly links business objectives and data, empowering readers to prioritize and drive effective data quality initiatives.The strength of this book lies in its practicality, offering real-world examples and reusable templates that expedite the implementation of data quality improvements. The author guides readers through every stage of the data quality lifecycle, from creating a compelling business case to seamlessly embedding lasting changes within the organization. The inclusion of tried-and-tested reports facilitates the identification and correction of bad data, ensuring tangible results.Overall, "Practical Data Quality" is a must-read for anyone serious about leveraging the benefits of improved data in processes and decision-making. Its real-world focus, coupled with actionable insights and templates, earns it a well-deserved five-star rating.
Amazon Verified review Amazon
Ravinder Pal Vashist Nov 21, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book covers Data quality management practices and covers all fundamentals require to start DQ Management at enterprise level.Must read book for any DQ professional and covers all topics in details for end to end implementation of DQM solutions. Highly recommended for students pursuing DQ Courses.
Amazon Verified review Amazon
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