Description: FASTSHIPPING HASSLEFREERETURNS SECUREPAYMENT EXCELLENTSERVICE 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 Publisher : O'Reilly Media Language : English Paperback : 308 pages ISBN-10 : 1098112040 ISBN-13 : 978-1098112042 Item Weight : 1.15 pounds Dimensions : 7 x 0.75 x 9 inches SHIPPING Shipping All items fast! The majority of orders are shipped using USPS Priority Mail and UPS Ground if requested. There is an option at checkout to add a Signature of Delivery for extra security & peace of mind. This means you need to sign for your parcel. If you are not home, the courier will take it to your local post office for collection. 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Price: 55.12 USD
Location: Philadelphia, Pennsylvania
End Time: 2025-01-01T20:48:02.000Z
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Restocking Fee: No
Return shipping will be paid by: Seller
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money back or replacement (buyer's choice)
Subject: Data Quality Fundamentals: A Practitioner's.. PAPERBACK
ISBN: 1098112040
Item Length: 9.3in
Item Height: 0.7in
Item Width: 7in
Author: Lior Gavish, Molly Vorwerck, Barr Moses
Publication Name: Data Quality Fundamentals : a Practitioner's Guide to Building Trustworthy Data Pipelines
Format: Trade Paperback
Language: English
Publisher: O'reilly Media, Incorporated
Publication Year: 2022
Type: Textbook
Item Weight: 18.2 Oz
Number of Pages: 308 Pages