Book Image

Data Engineering with Python

By : Paul Crickard
Book Image

Data Engineering with Python

By: Paul Crickard

Overview of this book

Data engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.
Table of Contents (21 chapters)
Section 1: Building Data Pipelines – Extract Transform, and Load
Section 2:Deploying Data Pipelines in Production
Section 3:Beyond Batch – Building Real-Time Data Pipelines

Chapter 8: Version Control with the NiFi Registry

In the previous chapters, you built several data pipelines, but we have left out a very important component—version control. Any good software developer will almost always set up version control on their project before they start writing any code. Building data pipelines for production is no different. Data engineers use many of the same tools and processes as software engineers. Using version control allows you to make changes without the fear of breaking your data pipeline. You will always be able to roll back changes to previous versions. The NiFi registry also allows you to connect new NiFi instances and have full access to all your existing data pipelines. In this chapter, we're going to cover the following main topics:

  • Installing and configuring the NiFi Registry
  • Using the Registry in NiFi
  • Versioning your data pipelines
  • Using git-persistence with the NiFi Registry