O’Reilly’s Book
O’Reilly’s Book | Automating Data Quality Monitoring at Scale

Free Early Release of Chapters 1 and 2

Get Early Access to Chapters 1 and 2

Available Now! Get Early Access to Chapters 1 and 2

Thank You. We Will Contact You Shortly.

Oops! Something went wrong while submitting the form.

We’re excited to share the first two chapters of our O’Reilly book, Automating Data Quality Monitoring at Scale.

Chapter 1 explains the importance of data quality and what can go wrong when issues with data aren’t discovered and resolved quickly. Now, with the addition of Chapter 2, you’ll learn about the past, present, and future of data quality monitoring strategies. You’ll discover:

  • What data quality monitoring should accomplish, and why it must go beyond basic observability
  • The pros and cons of the three main historical approaches:
    • Manual checks
    • Rule-based testing
    • Metrics monitoring
  • How machine learning can scale data quality monitoring while reducing false positives and alert fatigue
  • The drawbacks of relying exclusively on machine learning
  • How combining human expertise and automation yields a best-of-all-worlds approach

You will learn the following

How bad data quality can erode an organization’s trust
What matters most in this new decade of data
Why data quality risks grow exponentially

About the Authors

Jeremy Stanley

Co-Founder and CTO at Anomalo

Prior to Anomalo, Jeremy was the VP of Data Science at Instacart, where he led machine learning and drove multiple initiatives to improve the company's profitability. He’s applied machine learning and AI technologies to everything from insurance and accounting to ad-tech and last-mile delivery logistics.

Previously, he led data science and engineering at other hyper-growth companies like Sailthru. He’s also a recognized thought leader in the data science community with hugely popular blog posts like Deep Learning with Emojis (not Math). Jeremy holds a BS in Mathematics from Wichita State University and an MBA from Columbia University.

Paige Schwartz

Head of Content at Anomalo

Paige has worked with clients such as Airbnb, Grammarly, and Samsara, as well as successful startups like CodeSignal, Tecton, Clerky, and Fiddler.

She specializes in communicating complex software engineering topics to a general audience and has spent her career working with machine learning and data systems, including 5 years as a product manager on Google Search. She holds a joint BA in Computer Science and English from UC Berkeley.

© 2023 Anomalo, Inc.Typography