Read Data Quality Fundamentals

Data Quality Fundamentals

Unknown Author

4.9/5 (9822 ratings)

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 assetsWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Data Quality Fundamentals. To get started finding Data Quality Fundamentals, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: 288

Format: PDF, EPUB & Kindle Edition

Publisher: O'Reilly Media, Inc.

Release: 2022

ISBN: 1098112024

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 assetsWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Data Quality Fundamentals. To get started finding Data Quality Fundamentals, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Special Offer | $0.00

Special Offer! | $0.00

Data Quality Fundamentals

Data Quality Fundamentals

More Books