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Data Observability for Data Engineering

Data Observability for Data Engineering

By : Michele Pinto, Sammy El Khammal
4.7 (3)
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Data Observability for Data Engineering

Data Observability for Data Engineering

4.7 (3)
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)
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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

Data Observability Checklist

We have seen that data observability has the capability to become an important component in your data projects. It enables organizations to gain real-time insights into the behavior of their systems and infrastructure, allowing for faster troubleshooting, improved performance, and better decision-making.

However, implementing data observability can also present a number of challenges and pitfalls. After having conducted several data observability projects across different industry sectors, we wanted to share with you some points of attention to make your journey toward data observability successful.

In this chapter, we will explore the perks and drawbacks of data observability, providing guidance on how to implement it effectively while avoiding common pitfalls. We will see how data observability projects may fail, and what the strategies to overcome this are.

By the end of this chapter, you will have a deeper understanding of the challenges of...

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Data Observability for Data Engineering
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