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Modern Data Architectures with Python

You're reading from   Modern Data Architectures with Python A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781801070492
Length 318 pages
Edition 1st Edition
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Author (1):
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Brian Lipp Brian Lipp
Author Profile Icon Brian Lipp
Brian Lipp
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1:Fundamental Data Knowledge
2. Chapter 1: Modern Data Processing Architecture FREE CHAPTER 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

Completing Our Project

So, we are at the end of the project, and we now need to add meat to our work. We have built the scaffold of our project, but we don’t really have anything else at the moment. We still need to create code for all of our apps. When we have done this, we will deploy the code to the public PyPI servers. This will be critical because we are now going to pull our pipeline code from a code repository, which is the ideal scenario. We will also set up CI for our code, which will do the checking and scanning of our code. Given the limited space, we will not be covering deployment using the CI of pipeline code, but this is the next step in that process. We will also cover schema management and some limited data governance. The goal is to have a working example of a data pipeline that is in line with something you would see in production.

This chapter covers the following topics:

  • Documentation
  • Faking data with Mockaroo
  • Managing our schemas with...
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