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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

Concepts

Author (1):

Brian Lipp

Table of Contents (19) Chapters

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

Why subscribe?

18. Other Books You May Enjoy

Summary

We covered a lot of material. To summarize, we talked about the importance of data visualizations and how to create them using a variety of tooling. We went over tips and tricks for notebooks in Databricks. We delved into SQL analytics and connecting BI Tools such as Tableau and DBT. With the knowledge you now possess, you should be able to design and implement complex data visualization systems.

In the upcoming chapter, we will see how to organize our data projects and build them into continuous integration projects using Jenkins and GitHub. As we write our code, we will look at techniques for automating checks of our code. We will then discuss how to deploy our code into production.

The rest of the chapter is locked

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Authors (1)

Brian Lipp

Brian Lipp is a Technology Polyglot, Engineer, and Solution Architect with a wide skillset in many technology domains. His programming background has ranged from R, Python, and Scala, to Go and Rust development. He has worked on Big Data systems, Data Lakes, data warehouses, and backend software engineering. Brian earned a Master of Science, CSIS from Pace University in 2009. He is currently a Sr. Data Engineer working with large Tech firms to build Data Ecosystems.

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