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Modern Data Architectures with Python

You're reading from  Modern Data Architectures with Python

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781801070492
Pages 318 pages
Edition 1st Edition
Languages
Author (1):
Brian Lipp Brian Lipp
Profile icon Brian Lipp
Toc

Table of Contents (19) Chapters close

Preface 1. Part 1:Fundamental Data Knowledge
2. Chapter 1: Modern Data Processing Architecture 3. Chapter 2: Understanding Data Analytics 4. Part 2: Data Engineering Toolset
5. Chapter 3: Apache Spark Deep Dive 6. Chapter 4: Batch and Stream Data Processing Using PySpark 7. Chapter 5: Streaming Data with Kafka 8. Part 3:Modernizing the Data Platform
9. Chapter 6: MLOps 10. Chapter 7: Data and Information Visualization 11. Chapter 8: Integrating Continous Integration into Your Workflow 12. Chapter 9: Orchestrating Your Data Workflows 13. Part 4:Hands-on Project
14. Chapter 10: Data Governance 15. Chapter 11: Building out the Groundwork 16. Chapter 12: Completing Our Project 17. Index 18. Other Books You May Enjoy

CI tooling

When making the development transition to a more organized project, the tooling we will go through is organized around what is known as the software development life cycle. This is generally understood as the preferred path when writing software. This life cycle isn’t always a good fit – for example, in research-style projects such as data science projects.

We have set up a large number of tools, but let’s now take a look first at Git and GitHub.

Git and GitHub

Source control is a fundamental component in writing software and managing technology. When you write your code, you check it into source control. When you are ready to bring that code into the main branch, you create a pull request. A pull request is a process where other members of the team will review your code, discuss portions of that code, and work together with you. The output of a pull request is confidence in the new feature you are bringing into your project.

Let’s...

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