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

Inserting and extracting relational data in Python

When you hear the word database, you probably picture a relational database – that is, a database made up of tables containing columns and rows with relationships between the tables; for example, a purchase order system that has inventory, purchases, and customer information. Relational databases have been around for over 40 years and come from the relational data model developed by E. F. Codd in the late 1970s. There are several vendors of relational databases – including IBM, Oracle, and Microsoft – but all of these databases use a similar dialect of SQL, which stands for Structured Query Language. In this book, you will work with a popular open source database – PostgreSQL. In the next section, you will learn how to create a database and tables.

Creating a PostgreSQL database and tables

In Chapter 2, Building Our Data Engineering Infrastructure, you created a database in PostgreSQL using pgAdmin...