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Data Quality Fundamentals

By Barr Moses

Data Quality Fundamentals Computer Science

Data Quality Fundamentals

Only 1 item left in stock
Description
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
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
308
Release Date:
2022-10-11
Publication Date:
2022-10-11
Publisher:
O'Reilly Media
Languages:
Original: English
ISBN10:
1098112040
ISBN13:
9781098112042
GPSR Manufacturer Reference:
[email protected]
Weight:
550 g
Height:
176 cm
Width:
230 cm
Thickness:
17 cm

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Very good
Almost no signs of wear. Book pages have no markings, accessories are intact and all other media are in good condition.
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