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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

Challenges of implementing data observability

In this section, we will describe the common pitfalls and challenges of the implementation of data observability and how we can overcome them. The concerns we will cover are the following:

  • Costs
  • Overhead
  • Security
  • Complexity increase
  • Legacy system
  • Information overload

Let’s start with the bottom line: the costs.

Costs

Foremost among the concerns surrounding data observability are its associated costs, which can pose a significant financial burden on data projects. These expenses typically encompass the following:

  • The acquisition or development costs of a data observability solution, including the investment in research and development and the requisite team training
  • Expenses related to the storage and computation of data observations, which can also introduce overhead, as we will elaborate on later in this chapter
  • The marginal cost incurred when integrating observability into...
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