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 1: What is Data Engineering?

Welcome to Data Engineering with Python. While data engineering is not a new field, it seems to have stepped out from the background recently and started to take center stage. This book will introduce you to the field of data engineering. You will learn about the tools and techniques employed by data engineers and you will learn how to combine them to build data pipelines. After completing this book, you will be able to connect to multiple data sources, extract the data, transform it, and load it into new locations. You will be able to build your own data engineering infrastructure, including clustering applications to increase their capacity to process data.

In this chapter, you will learn about the roles and responsibilities of data engineers and how data engineering works to support data science. You will be introduced to the tools used by data engineers, as well as the different areas of technology that you will need to be proficient in to...