Data Quality Fundamentals: A Practitioner’s Guide to Building Trustworthy Data Pipelines

Author: Barr Moses

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9789355421753
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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
    Books
    Author
    Barr Moses
    Author 2
    Lior Gavish
    Author 3
    Molly Varwerck
    Binding
    Paperback
    Condition Type
    New
    Country Origin
    India
    Edition
    First
    Gift Wrap
    N
    Lead time to ship in days (if not in stock)
    ships in 12-15 days
    Leadtime to ship in days (default)
    ships in 1-2 days
    Pages
    312
    Publication Date
    27/09/2022
    Publisher
    Shroff/O'Reilly
    Year
    2022
    Dimensions
    Dimensions (W x H x D)
    7 x 9 x 0.6 inch

    Table of Contents (9789355421753_toc.pdf, 50 Kb) [Download]

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