Managing data workflows can be time-consuming and complex, especially when you need to integrate multiple data sources and automate tasks. In this course, Build and Deploy ETL Pipelines with Python, will teach you how to efficiently build automated data workflows. First, you’ll explore how to extract data by connecting to databases and raw files using Python and retrieve data through various methods, including SQL queries and database connectors. Next, you’ll discover how to extract data from REST APIs and parse responses, allowing you to pull data from web services into your pipeline. Finally, you’ll learn how to automate and schedule ETL tasks, saving time and reducing manual intervention. When you’re finished with this course, you’ll have the skills and knowledge needed to design and automate end-to-end ETL pipelines that connect to databases, integrate with REST APIs, and run on schedule, all using Python.
Overview
Managing data workflows can be time-consuming and complex, especially when you need to integrate multiple data sources and automate tasks. In this course, Build and Deploy ETL Pipelines with Python, will teach you how to efficiently build automated data workflows. First, you’ll explore how to extract data by connecting to databases and raw files using Python and retrieve data through various methods, including SQL queries and database connectors. Next, you’ll discover how to extract data from REST APIs and parse responses, allowing you to pull data from web services into your pipeline. Finally, you’ll learn how to automate and schedule ETL tasks, saving time and reducing manual intervention. When you’re finished with this course, you’ll have the skills and knowledge needed to design and automate end-to-end ETL pipelines that connect to databases, integrate with REST APIs, and run on schedule, all using Python.
Taught by
Ian Fogelman
