Data Observability for Data Engineering
Proactive strategies for ensuring data accuracy and addressing broken data pipelines
Created by Michele Pinto, Sammy El Khammal
Gain practical skills to monitor and validate the health of your data pipelines. Discover how to spot and fix issues before they impact your organization, and build trust in your data by applying proven observability techniques.
Packt | Dec 2023 | 228 min
What You Will Learn
You will explore core concepts of data observability and see how they apply to real-world data engineering challenges. Through hands-on coding exercises and practical use cases, you will learn to collect metrics, analyze pipeline health, and implement monitoring strategies that scale with your needs.
Key Features
- Monitor and validate data pipelines to catch issues early and ensure reliability
- Apply observability techniques directly in Python for hands-on problem solving
- Build confidence in your data by making pipelines transparent and trustworthy
Target Audience
Designed for data engineers, analysts, architects, and scientists who want to prevent broken pipelines and improve data quality. If you are responsible for managing or maintaining data processes and want to build trust in your data, you will benefit from these actionable strategies and skills.
