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Quickly detect, troubleshoot, and prevent a wide range of data issues through data observability, a set of best practices that enables data teams to gain greater visibility of data and its usage. If you're a data engineer, data architect, or machine learning engineer who depends on the quality of your data, this book shows you how to focus on the practical aspects of introducing data observability in your everyday work.
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Book Details
Publication Year
2023
Contributors
Author Info
Andy Petrella has been in the data industry for almost 20 years, starting his career as a software engineer and data miner in the GIS space. He has evangelized big data for more than a decade, especially Apache Spark for which he created the Spark-Notebook (that has 3100 stars on Github).
University Books Details
Specialization
DATA OBSERVABILITY
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