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Data Observability for Data Engineering

You're reading from   Data Observability for Data Engineering Proactive strategies for ensuring data accuracy and addressing broken data pipelines

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781804616024
Length 228 pages
Edition 1st Edition
Languages
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Authors (2):
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Michele Pinto Michele Pinto
Author Profile Icon Michele Pinto
Michele Pinto
Sammy El Khammal Sammy El Khammal
Author Profile Icon Sammy El Khammal
Sammy El Khammal
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Introduction to Data Observability
2. Chapter 1: Fundamentals of Data Quality Monitoring FREE CHAPTER 3. Chapter 2: Fundamentals of Data Observability 4. Part 2: Implementing Data Observability
5. Chapter 3: Data Observability Techniques 6. Chapter 4: Data Observability Elements 7. Chapter 5: Defining Rules on Indicators 8. Part 3: How to adopt Data Observability in your organization
9. Chapter 6: Root Cause Analysis 10. Chapter 7: Optimizing Data Pipelines 11. Chapter 8: Organizing Data Teams and Measuring the Success of Data Observability 12. Part 4: Appendix
13. Chapter 9: Data Observability Checklist 14. Chapter 10: Pathway to Data Observability 15. Index 16. Other Books You May Enjoy

Defining and understanding data teams

In recent years, investment in data platforms and tools has grown exponentially. At the same time, and proportionally, investment in data teams has increased to the point where the number of data teams is in the hundreds and even thousands.

On the one hand, this has been and continues to be an exciting time for the data ecosystem and for those who work in it, but on the other hand, this exponential growth has also brought with it a whole new set of challenges, not only technical but also organizational. Over the years, several questions have spontaneously risen:

  • How can I scale a data team?
  • What skills and roles are required for the success of my data investment?
  • How does management, such as the hiring process and budget, differ for these specific roles?
  • How can I improve communication between my data team and the rest of the organization?

These are non-trivial questions that are difficult to answer. Simply put, we...

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