Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines - Softcover

Moses, Barr

Softcover

ISBN 10: 1098112040 ISBN 13: 9781098112042

Publisher: O'Reilly Media, 2022

Synopsis

Do your product dashboards look funky? Are your quarterly reports stale? Is the data set you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to any of these questions, this book is for you. Authors Barr Moses, Lior Gavish, and Molly Vorwerck explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies.

About this title

About the Author

Barr Moses is the CEO and co-founder of Monte Carlo, a data reliability company. In her decade-long career in data, Barr has served as commander of a data intelligence unit in the Israeli Air Force, a consultant at Bain & Company, and VP of Operations at Gainsight, where she built and led their data and analytics team. The instructor of O'Reilly first course on Data Observability, an emerging discipline in data engineering, Barr has worked with hundreds of data teams struggling with these problems. Inspired by her time in the analytics trenches, she is building a product literally dedicated to identifying, resolving, and preventing what she calls "data downtime," periods of time when data is missing, erroneous, or otherwise inaccurate. In other words: bad data. In this book, she shares her experiences and learnings on how today's data organizations can achieve high data quality at scale through technological, organization, and cultural best practices. Lior Gavish is CTO and Co-Founder of Monte Carlo, a data reliability company backed by Accel, Redpoint, GGV, and other top Silicon Valley investors. Prior to Monte Carlo, Lior co-founded cybersecurity startup Sookasa, which was acquired by Barracuda in 2016. At Barracuda, Lior was SVP of Engineering, launching award-winning ML products for fraud prevention. Lior holds an MBA from Stanford and an MSC in Computer Science from Tel-Aviv University. Molly Vorwerck is the Head of Content at Monte Carlo, a data reliability company. Prior to joining Monte Carlo, Molly served as editor-in-chief of the Uber Engineering Blog and lead program manager for Uber's Technical Brand team, where she spent countless hours helping engineers, data scientists, and analysts write and edit content about their technical work and experiences. She also led internal communications for Uber's Chief Technology Officer and strategy for Uber AI's Research Review Program. In her spare time, she freelances for USA Today, reads up on all the latest trends in data, and volunteers for the California Historical Society.

Edition details

• Publisher: O'Reilly Media
• Publication date: 2022
• Language: English
• ISBN 10: 1098112040
• ISBN 13: 9781098112042
• Binding: Paperback
• Number of pages: 80