Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines by Barr Moses, Lior Gavish, Molly Vorwerck, Barr Moses, Lior Gavish, Molly Vorwerck

Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines
Barr Moses, Lior Gavish, Molly Vorwerck, Barr Moses, Lior Gavish, Molly Vorwerck
Page: 308
Format: pdf, ePub, mobi, fb2
ISBN: 9781098112042
Publisher: O'Reilly Media, Incorporated
Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines

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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

A Practitioner's Guide to Building Trustworthy Data Pipelines
        Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Many data engineering teams today face the good pipelines, bad data problem.
        A Practitioner's Guide to Building Trustworthy Data Pipelines
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        A Practitioner's Guide to Building Trustworthy Data Pipelines
        Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines. Barr Moses, Lior Gavish, Molly Vorwerck.
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        Build more trustworthy and reliable data pipelines; Write scripts to make data checks and identify broken pipelines with data observability; Learn how to 
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