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


In this chapter, you learned how to process CSV and JSON files using Python. Using this new skill, you have created a data pipeline in Apache Airflow by creating a Python function to process a CSV and transform it into JSON. You should now have a basic understanding of the Airflow GUI and how to run DAGs. You also learned how to build data pipelines in Apache NiFi using processors. The process for building more advanced data pipelines is the same, and you will learn the skills needed to accomplish this throughout the rest of this book.

In the next chapter, you will learn how to use Python, Airflow, and NiFi to read and write data to databases. You will learn how to use PostgreSQL and Elasticsearch. Using both will expose you to standard relational databases that can be queried using SQL and NoSQL databases that allow you to store documents and use their own query languages.