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Data Engineering with Python

You're reading from  Data Engineering with Python

Product type Book
Published in Oct 2020
Publisher Packt
ISBN-13 9781839214189
Pages 356 pages
Edition 1st Edition
Languages
Author (1):
Paul Crickard Paul Crickard
Profile icon Paul Crickard

Table of Contents (21) Chapters

Preface 1. Section 1: Building Data Pipelines – Extract Transform, and Load
2. Chapter 1: What is Data Engineering? 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

Staging and validating data

When building production data pipelines, staging and validating data become extremely important. While you have seen basic data validation and cleaning in Chapter 5, Cleaning, Transforming, and Enriching Data, in production, you will need a more formal and automated way of performing these tasks. The next two sections will walk you through how to accomplish staging and validating data in production.

Staging data

In the NiFi data pipeline examples, data was extracted, and then passed along a series of connected processors. These processors performed some tasks on the data and sent the results to the next processor. But what happens if a processor fails? Do you start all over from the beginning? Depending on the source data, that may be impossible. This is where staging comes in to play. We will divide staging in to two different types: the staging of files or database dumps, and the staging of data in a database that is ready to be loaded into a warehouse...

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