Book Image

Data Observability for Data Engineering

By : Michele Pinto, Sammy El Khammal
Book Image

Data Observability for Data Engineering

By: Michele Pinto, Sammy El Khammal

Overview of this book

In the age of information, strategic management of data is critical to organizational success. The constant challenge lies in maintaining data accuracy and preventing data pipelines from breaking. Data Observability for Data Engineering is your definitive guide to implementing data observability successfully in your organization. This book unveils the power of data observability, a fusion of techniques and methods that allow you to monitor and validate the health of your data. You’ll see how it builds on data quality monitoring and understand its significance from the data engineering perspective. Once you're familiar with the techniques and elements of data observability, you'll get hands-on with a practical Python project to reinforce what you've learned. Toward the end of the book, you’ll apply your expertise to explore diverse use cases and experiment with projects to seamlessly implement data observability in your organization. Equipped with the mastery of data observability intricacies, you’ll be able to make your organization future-ready and resilient and never worry about the quality of your data pipelines again.
Table of Contents (17 chapters)
1
Part 1: Introduction to Data Observability
4
Part 2: Implementing Data Observability
8
Part 3: How to adopt Data Observability in your organization
12
Part 4: Appendix

Optimizing Data Pipelines

The importance of data in companies has significantly increased the investments in data platforms by companies. Over time, this has increased companies’ priority of being aware of what their data pipelines do and how they do it and therefore monitoring not only the quality of the outcomes but also the state of health of the pipelines. At the same time, they are also monitoring the usage of the resources and tracking the associated costs.

In this chapter, we will understand how data observability offers us a way to make the governance of our data pipelines scalable and sustainable. First, we will focus on understanding the key data pipelines, their main components, and the types of data pipelines, as well as their characteristics. Then, we will learn how data observability and, in particular, data lineage can be used to manage several aspects of the data pipeline life cycle, such as the costs and the risks.

In this chapter, we’ll cover the...