Now Available: O’Reilly Data Quality Fundamentals, Chapter 3

On behalf of the entire company, I’m excited to announce the release of Chapter 3 of Data Quality Fundamentals: A Practitioner’s Guide to Building More Trustworthy Data Pipelines, published by O’Reilly Media and available for free on the Monte Carlo website. This is the first book published by O’Reilly to educate the market on how best-in-class data teams design and architect technical systems to achieve trustworthy and reliable data at scale. 

O’Reilly’s Data Quality Fundamentals is the only guide of its kind to help data engineers and analysts understand the key factors that contribute to unreliable data pipelines and poor data quality, leverage new and novel processes and technologies to solve these problems, and design resilient, observable systems to prevent data downtime from happening in the first place. 

In Chapters 1-2, we discussed why data quality deserves attention today, and walked through how data engineers and analysts can architect more reliable data ecosystems, from ingestion in the warehouse or lake to the analytics layer downstream.

In Chapter 3, you’ll learn what it takes to identify, alert for, resolve, and prevent data quality issues in a holistic and end-to-end way across your stack.

We’ll discuss:

And much more!

The book is co-authored by Barr Moses, CEO, and co-founder of Monte Carlo, Lior Gavish, CTO and co-founder of Monte Carlo, and Molly Vorwerck, Head of Content at Monte Carlo and former lead editor of the Uber Engineering Blog. 

Get Free Access Today

We’re excited to share the first three chapters of Data Quality Fundamentals (a $67 value) with you for free, below!