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Data Observability for Data Engineering

You're reading from  Data Observability for Data Engineering

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781804616024
Pages 228 pages
Edition 1st Edition
Languages
Authors (2):
Michele Pinto Michele Pinto
Profile icon Michele Pinto
Sammy El Khammal Sammy El Khammal
Profile icon Sammy El Khammal
View More author details

Table of Contents (17) Chapters

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

Concepts of data pipelines and data architecture

We rarely think about how water reaches the taps of our homes. After all, we are end users who pay and use the service with certain expectations and have little visibility and interest in what concerns the transport and management of drinking water.

But this is a good moment to stop for a few seconds to understand this process – it is a process that has many similarities with data pipelines.

What is a data pipeline?

To better understand what a data pipeline is, we can compare it to the components that carry water from the basins to our homes:

  • There is a basin of water to draw from (the data sources)
  • Various mechanisms are needed to recover, purify, and transport water (the data applications)
  • The water reaches the taps of our houses (the data destination)

At this stage, let’s define what a data pipeline is. It is the flow of data that starts from one or several places where data is stored...

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