Data Quality Fundamentals 5th Edition by Barr Moses 9781098111991 1098111990

Data Quality Fundamentals 5th Edition Barr Moses – Ebook Instant Download/Delivery ISBN(s): 9781098112042,1098112040, 9781098111991, 1098111990

Product details:

• ISBN 10: 1098111990
• ISBN 13: 9781098111991
• Author: Barr Moses 

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

Table contents:

1. Why Data Quality Deserves Attention—Now

2. Assembling the Building Blocks of a Reliable Data System

3. Collecting, Cleaning, Transforming, and Testing Data

4. Monitoring and Anomaly Detection for Your Data Pipelines

5. Architecting for Data Reliability

6. Fixing Data Quality Issues at Scale

7. Building End-to-End Lineage

8. Democratizing Data Quality

9. Data Quality in the Real World: Conversations and Case Studies

10. Pioneering the Future of Reliable Data Systems

People also search:

data quality fundamentals o’reilly pdf

data quality fundamentals monte carlo

fundamentals of spatial data quality pdf

fundamentals of spatial data quality

5 characteristics of data quality