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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

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781839214189
Length 356 pages
Edition 1st Edition
Languages
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Author (1):
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Paul Crickard Paul Crickard
Author Profile Icon Paul Crickard
Paul Crickard
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Toc

Table of Contents (21) Chapters Close

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 Appendix

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

This section will introduce you to the basics of data engineering. In this section, you will learn what data engineering is and how it relates to other similar fields, such as data science. You will cover the basics of working with files and databases in Python and using Apache NiFi. Once you are comfortable with moving data, you will be introduced to the skills required to clean and transform data. The section culminates with the building of a data pipeline to extract 311 data from SeeClickFix, transform it, and load it into another database. Lastly, you will learn the basics of building dashboards with Kibana to visualize the data you have loaded into your database.

This section comprises the following chapters:

  • Chapter 1, What is Data Engineering?
  • Chapter 2, Building Our Data Engineering Infrastructure
  • Chapter 3, Reading and Writing Files
  • Chapter 4, Working with Databases
  • Chapter...
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