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Data Engineering with Python

You're reading from Data Engineering with Python Work with massive datasets to design data models and automate data pipelines using Python

Product type Paperback

Published in Oct 2020

Publisher Packt

ISBN-13 9781839214189

Length 356 pages

Edition 1st Edition

Languages

Python

Concepts

Data Analysis

Author (1):

Paul Crickard

View More author details

Table of Contents (21) Chapters

Preface

1. Section 1: Building Data Pipelines – Extract Transform, and Load

2. Chapter 1: What is Data Engineering? FREE CHAPTER

3. Chapter 2: Building Our Data Engineering Infrastructure

4. Chapter 3: Reading and Writing Files

5. Chapter 4: Working with Databases

6. Chapter 5: Cleaning, Transforming, and Enriching Data

7. Chapter 6: Building a 311 Data Pipeline

8. Section 2:Deploying Data Pipelines in Production

9. Chapter 7: Features of a Production Pipeline

10. Chapter 8: Version Control with the NiFi Registry

11. Chapter 9: Monitoring Data Pipelines

12. Chapter 10: Deploying Data Pipelines

13. Chapter 11: Building a Production Data Pipeline

14. Section 3:Beyond Batch – Building Real-Time Data Pipelines

15. Chapter 12: Building a Kafka Cluster

16. Chapter 13: Streaming Data with Apache Kafka

17. Chapter 14: Data Processing with Apache Spark

18. Chapter 15: Real-Time Edge Data with MiNiFi, Kafka, and Spark

19. Other Books You May Enjoy

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Appendix

Download the example code files

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Authors (1)

Paul Crickard

Paul Crickard

Paul Crickard authored a book on the Leaflet JavaScript module. He has been programming for over 15 years and has focused on GIS and geospatial programming for 7 years. He spent 3 years working as a planner at an architecture firm, where he combined GIS with Building Information Modeling (BIM) and CAD. Currently, he is the CIO at the 2nd Judicial District Attorney's Office in New Mexico.

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