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Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data

Description: Do your product dashboards look funky? Are your quarterly reports stale? Is the dataset 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 any of the questions above, 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 reliability 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 Program your own data quality monitors from scratch Develop and lead data quality initiatives at your company Generate a dashboard to highlight your company's key data assets Automate data lineage graphs across your data ecosystem Build anomaly detectors for your critical data assets

Price: 49.65 USD

Location: East Hanover, NJ

End Time: 2024-12-30T11:25:50.000Z

Shipping Cost: 0 USD

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Data Quality Fundamentals: A PractitionerData Quality Fundamentals: A Practitioner

Item Specifics

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 60 Days

Refund will be given as: Money back or replacement (buyer's choice)

Return policy details:

EAN: 9781098112042

UPC: 9781098112042

ISBN: 9781098112042

MPN: N/A

Book Title: Data Quality Fundamentals: A Practitioner's Guide

Number of Pages: 308 Pages

Language: English

Publication Name: Data Quality Fundamentals : a Practitioner's Guide to Building Trustworthy Data Pipelines

Publisher: O'reilly Media, Incorporated

Publication Year: 2022

Item Height: 0.7 in

Subject: Desktop Applications / Databases, Data Processing, Databases / Data Mining

Item Weight: 18.2 Oz

Type: Textbook

Item Length: 9.3 in

Author: Lior Gavish, Molly Vorwerck, Barr Moses

Subject Area: Computers

Item Width: 7 in

Format: Trade Paperback

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