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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
Authors (2):
Michele Pinto Michele Pinto
Profile icon Michele Pinto
Sammy El Khammal Sammy El Khammal
Profile icon 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

Turning SLOs into rules

In this section, we will see how objectives can be turned into actionable rules by creating contextual checkpoints from the pipeline or externally. At the start of any rule is the expectation, which can be defined as "What does the consumer expect from the dataset?"

An expectation formalizes the objective into a rule and the corresponding metric to be tracked. The expectation is then a good way to document the objectives and the metrics needed to respect them. The two components of the expectation have their importance: the rule tells the observer how the data should behave, and the metric is used to detect whether the behavior is deviant or not.

Let’s look at the different types of rules that we can set.

Different types of rules

The backbone of a rule is the indicator. Based on this, a rule can be set and will start checking how the metric is behaving. These rules are often guided by the principles of data quality discussed in Chapter...

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