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Data Observability for Data Engineering

You're reading from  Data Observability for Data Engineering

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781804616024
Pages 228 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Michele Pinto Michele Pinto
Profile icon Michele Pinto
LinkedIn
Michele Pinto is the Head of Engineering at Kensu. With over 15 years of experience, Michele has a great knack for understanding how data observability and data engineering are closely linked. He started his career as a software engineer and has worked since then in various roles, such as big data engineer, big data architect, head of data and until recently he was a Head of Engineering. He has a great community presence and believes in giving back to the community. He has also been a teacher for Digital Product Management Master TAG Innovation School in Milan, Italy. His collaboration on the book has been prompt, swift, eager, and very invested.
See other products by Michele Pinto
Sammy El Khammal Sammy El Khammal
Profile icon Sammy El Khammal
LinkedIn
Sammy El Khammal works at Kensu. He started off as a field engineer and worked his way up to the position of product manager. In the past, he has also worked with Mercedes as their Business Development Analyst – Intern. He has also been an O'Reilly teacher for 3 workshops on data quality, lineage monitoring, and data observability. During that time, he provided some brilliant insights, very responsive behaviour, and immense talent and determination.
See other products by Sammy El Khammal
View More author details

Table of Contents (17) Chapters

Preface Part 1: Introduction to Data Observability
Chapter 1: Fundamentals of Data Quality Monitoring Chapter 2: Fundamentals of Data Observability Part 2: Implementing Data Observability
Chapter 3: Data Observability Techniques Chapter 4: Data Observability Elements Chapter 5: Defining Rules on Indicators Part 3: How to adopt Data Observability in your organization
Chapter 6: Root Cause Analysis Chapter 7: Optimizing Data Pipelines Chapter 8: Organizing Data Teams and Measuring the Success of Data Observability Part 4: Appendix
Chapter 9: Data Observability Checklist Chapter 10: Pathway to Data Observability Index Other Books You May Enjoy

Data observability in IT observability

Observability is not a new asset in the monitoring toolkit. Indeed, making a system observable is already implemented by the operational and DevOps community to report on application or system availability. Observability helps us to monitor complex distributed systems by collecting logs, metrics, or traces.

If we take observability in the broadest sense, every component of the data pipeline can be monitored — not only the data, but the application, the system, or even the users. Data observability helps us to build the bridge between the data engineering world and application and system observability, with some common elements allowing a deeper analysis of data issues in the context of full observability.

Besides the problems that come from the data itself, other issues may arise — for instance, from an unresized cluster, a failing or outdated application, and so on. The combination of all kinds of observability can increase...

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Authors (2)

Left arrow icon
Profile icon Michele Pinto
LinkedIn
Michele Pinto is the Head of Engineering at Kensu. With over 15 years of experience, Michele has a great knack for understanding how data observability and data engineering are closely linked. He started his career as a software engineer and has worked since then in various roles, such as big data engineer, big data architect, head of data and until recently he was a Head of Engineering. He has a great community presence and believes in giving back to the community. He has also been a teacher for Digital Product Management Master TAG Innovation School in Milan, Italy. His collaboration on the book has been prompt, swift, eager, and very invested.
Read more
See other products by Michele Pinto
Profile icon Sammy El Khammal
LinkedIn
Sammy El Khammal works at Kensu. He started off as a field engineer and worked his way up to the position of product manager. In the past, he has also worked with Mercedes as their Business Development Analyst – Intern. He has also been an O'Reilly teacher for 3 workshops on data quality, lineage monitoring, and data observability. During that time, he provided some brilliant insights, very responsive behaviour, and immense talent and determination.
See other products by Sammy El Khammal
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