Your pipelines are breaking. Your team is firefighting. Stakeholders no longer trust the numbers. No amount of new tooling fixes it.

The DataOps Guide to Data Quality and Observability cuts through the noise to tell you what's actually going wrong and what to do about it. Drawing on years of hard-won experience working with data teams across industries, this book exposes the cultural blind spots, dysfunction, and broken processes that keep data quality perpetually out of reach. Then it gives you a practical, battle-tested playbook to take back control.

From shift-left testing to continuous monitoring and pipeline observability, you’ll learn to prevent data disasters instead of just reacting. Better data quality isn’t a fantasy. It’s a discipline. This book shows you how to build it.