Chapters 1 & 2
O'Reilly | Fundamentals of Data Observability
Quickly detect, troubleshoot, and prevent the propagation of a wide range of data incidents through Data Observability, a set of best practices that allow data teams to gain greater visibility of data and its usage.
If you’re a data engineer, ML engineer, or data architect, or if the quality of your work depends on the quality of your data, this book shows how to focus on the practical aspects of introducing Data Observability in your day-to-day work.
Get the Chapters 1 & 2
What you will learn in this book
"Author Andy Petrella, Kensu's Founder, helps you build the right habits to detect and solve data issues, so you can stop their propagation in data applications, pipelines, and analytics. You’ll learn how to introduce data observability, including setting up a framework for generating and collecting all the information you need."
Discover the core principles and benefits of Data Observability
Use observability to identify, troubleshoot, and prevent data issues
Learn how to implement observability in your data projects
Create a trustable communication framework with data consumers
Educate your peers about the benefits of Data Observability
Who this book is for
This book is for data executives, data engineers, data architects, data analysts, and data scientists who are looking to improve data reliability, lower maintenance costs, and scale up data usage. It is also useful for organizations looking for a way to increase the confidence of consumers and the awareness of producers in their data pipelines.
About the Author
Founder and CPO @Kensu
Andy is an entrepreneur with a background in data mining, data engineering, and data science. He is known as an early evangelist of Apache Spark and the Spark Notebook creator in the data community.
Since 2015, Andy has been an O’Reilly instructor and author, including the first O’Reilly book about Data Observability.