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

Using git-persistence with the NiFi Registry

Just like software developers, you can also use Git to version control your data pipelines. The NiFi Registry allows you to use git-persistence with some configuration. To use Git with your data pipelines, you need to first create a repository.

Log in to GitHub and create a repository for your data pipelines. I have logged in to my account and have created the repository as shown in the following screenshot:

Figure 8.16 – Creating a GitHub repository

After creating a repository, you will need to create an access token for the registry to use to read and write to the repository. In the GitHub Settings, go to Developer settings, then Personal access tokens, then click the Generate a personal access token hyperlink shown in the following screenshot:

Figure 8.17 – The setting to create an access token

You can then add a note for the token so you can remember what service is using...