Part 2:Designing ETL Pipelines with Python

For the second part of this book, we will get into the data extraction, transformation, and loading activities within ETL data pipelines. We will start by going over how to extract data from various source systems, from files to APIs to databases. After that, we will deal with various data transformation techniques in Python, and then end by looking into some of the best practices for data loading. We close out this section by exploring various open source Python tools that you can use to enhance the efficiency and design of your data pipelines.

This section contains the following chapters:

• Chapter 4, Sourcing Insightful Data and Data Extraction Strategies
• Chapter 5, Data Cleansing and Transformation
• Chapter 6, Loading Transformed Data
• Chapter 7, Tutorial – Building an End-to-End ETL Pipeline in Python
• Chapter 8, Powerful ETL Libraries and Tools in Python