Limit search to available items
Book Cover
Author Moses, Barr, author.

Title Data quality fundamentals : a practitioner's guide to building trustworthy data pipelines / Barr Moses, Lior Gavish & Molly Vorwerck
Edition First edition
Published Sebastopol, CA : O'Reilly media, 2022


Description 1 online resource (xvi, 288 pages)
Summary 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 these questions, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck, from the data observability company Monte Carlo, 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. Build more trustworthy and reliable data pipelines Write scripts to make data checks and identify broken pipelines with data observability Learn how to set and maintain data SLAs, SLIs, and SLOs Develop and lead data quality initiatives at your company Learn how to treat data services and systems with the diligence of production software Automate data lineage graphs across your data ecosystem Build anomaly detectors for your critical data assets
Notes Includes index
Online resource; title from PDF title page (EBSCO, viewed December 6, 2022)
Subject Data mining.
Data mining.
Form Electronic book
Author Gavish, Lior, author
Vorwerck, Molly, author
ISBN 9781098112011