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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

Chapter 6: Building a 311 Data Pipeline

In the previous three chapters, you learned how to use Python, Airflow, and NiFi to build data pipelines. In this chapter, you will use those skills to create a pipeline that connects to SeeClickFix and downloads all the issues for a city, and then loads it in Elasticsearch. I am currently running this pipeline every 8 hours. I use this pipeline as a source of open source intelligence – using it to monitor quality of life issues in neighborhoods, as well as reports of abandoned vehicles, graffiti, and needles. Also, it's really interesting to see what kinds of things people complain to their city about – during the COVID-19 pandemic, my city has seen several reports of people not social distancing at clubs.

In this chapter, we're going to cover the following main topics:

  • Building the data pipeline
  • Building a Kibana dashboard
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