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.

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Spis treści

Data Observability for Data Engineering. Proactive strategies for ensuring data accuracy and addressing broken data pipelines eBook -- spis treści

• 1. Fundamentals of Data Quality Monitoring
• 2. Fundamentals of Data Observability
• 3. Data Observability techniques
• 4. Data Observability elements
• 5. Defining rules on indicators
• 6. Root cause analysis
• 7. Optimizing data pipelines
• 8. Introducing and changing culture in the team
• 9. Data observability checklist
• 10. Use Cases