Book Image

Practical Data Quality

By : Robert Hawker
Book Image

Practical Data Quality

By: Robert Hawker

Overview of this book

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.
Table of Contents (16 chapters)
Part 1 – Getting Started
Part 2 – Understanding and Monitoring the Data That Matters
Part 3 – Improving Data Quality for the Long Term

The future of data quality work

Up until this point, this book has been based entirely on my experience across the various organizations I have worked with. This final section is different. It is my conjecture and theory about how working in data quality will change over the next 10 years.

Over the last year, we have seen much wider public recognition of the potential of artificial intelligence (AI)-driven large language models (LLMs), such as OpenAI’s Chat-GPT. When combined with major ongoing growth in the perceived importance of data in organizations, there will be a significant shift in how we do data quality work in the future.

This section outlines the key trends I expect to see, and what we as data quality professionals need to do to be prepared.


LLMs are a capability driven by AI. They have been trained by being exposed to large quantities of publicly available information via the internet. This training and access to information allows them to respond...