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Data Observability for Data Engineering

You're reading from   Data Observability for Data Engineering Proactive strategies for ensuring data accuracy and addressing broken data pipelines

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781804616024
Length 228 pages
Edition 1st Edition
Languages
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Authors (2):
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Michele Pinto Michele Pinto
Author Profile Icon Michele Pinto
Michele Pinto
Sammy El Khammal Sammy El Khammal
Author Profile Icon Sammy El Khammal
Sammy El Khammal
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Introduction to Data Observability
2. Chapter 1: Fundamentals of Data Quality Monitoring FREE CHAPTER 3. Chapter 2: Fundamentals of Data Observability 4. Part 2: Implementing Data Observability
5. Chapter 3: Data Observability Techniques 6. Chapter 4: Data Observability Elements 7. Chapter 5: Defining Rules on Indicators 8. Part 3: How to adopt Data Observability in your organization
9. Chapter 6: Root Cause Analysis 10. Chapter 7: Optimizing Data Pipelines 11. Chapter 8: Organizing Data Teams and Measuring the Success of Data Observability 12. Part 4: Appendix
13. Chapter 9: Data Observability Checklist 14. Chapter 10: Pathway to Data Observability 15. Index 16. Other Books You May Enjoy

Defining Rules on Indicators

In the previous chapters, we saw how you could collect events synchronously in your data applications. We also discussed what contextual information you need in order to draw the big picture of what’s happening inside the applications.

Now that you have a lot of contextual information, it is high time to turn it into actionable insights. The metrics you collect during the pipeline execution need to reassure all the stakeholders about the proper execution of the data applications. All the observers of the pipeline need to be informed about how the data pipeline is behaving.

To maintain the trust of data producers and data consumers, we will introduce the concept of expectations, which will define what the engineer needs to achieve in order to keep the pipeline in good shape. These expectations, composed of metrics and rules, will act as sensors to know whether the applications are working as expected or not.

These rules are a key component...

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