Book review: Managing Data Quality – A practical guide

Where Practical Data Migration puts words to how you run a migration, this book is about why most migrations ultimately come down to a single thing: data quality. Managing Data Quality – A practical guide by Tim King and Julian Schwarzenbach (published by BCS, The Chartered Institute for IT) is one of the most useful books I've read in the field.

Why it's worth reading

A lot of what's written about data quality stops at "clean the data". This book does the opposite: it treats data quality as a capability and a discipline, not a one‑off effort. The authors are pragmatic – it's a practical guide, not an academic treatise – and they write for the person who actually has to get something done in a real organization.

The book is structured around four areas: the nature of data in enterprises, the impact of people, the purpose and scope of data quality management, and how to implement a data quality management system in practice – aligned with the international standard ISO 8000‑61. The authors' authority on the subject shows: Tim King is convener for the development of ISO 8000, and Julian Schwarzenbach is a Fellow of the BCS and Chair of the BCS Data Management Specialist Group.

What stuck with me

• Quality has dimensions. Accuracy, completeness, consistency, timeliness, uniqueness – breaking "quality" down into measurable dimensions turns it into something concrete you can steer toward, rather than a gut feeling.
• Measure, don't just treat symptoms. Cleaning the same error over and over is treating symptoms. The book pushes hard on root‑cause analysis – why does the error occur, and how do you stop it at the source?
• Data quality is a business issue. Just like migration: technology can measure and report, but ownership and decisions belong with the business.
• Build a business case. The authors are clear that data quality has to be justified in business terms – cost, risk, opportunity – to gain traction in an organization.

How it connects to my work

Data quality isn't a side issue in a migration – it's often the whole issue. In my post on why migrations fail, underestimated data quality is the single most common cause. The PDM methodology's "Data Quality Rules" and the thinking in this book complement each other well: one gives you the framework for the migration, the other the depth on how to actually measure and improve quality over time.

Who should read it?

Anyone who owns or works with business data – not just data quality specialists. It works equally well as an introduction for business people pulled into a data initiative as for those wanting to sharpen their own practice.

My takeaway

A short, concrete and surprisingly deep book. Read it alongside Practical Data Migration and you'll have both the how and the why in place. You'll find it on Amazon.

Want to raise data quality ahead of a system change? Get in touch – I'm happy to share.