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Course
- Data
Build and Deploy ETL Pipelines with Python
Learn to build efficient ETL pipelines with Python. This course will teach you how to connect databases, extract data from REST APIs, transform it, and automate workflows using scheduling tools.
What you'll learn
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.
Table of contents
About the author
Ian is a database enthusiast with particular expertise in the Microsoft data stack. Other technologies that Ian has expert level experience with include ETL, Python development, cloud architecture and systems automation. Ian holds the Microsoft Certified Solutions Expert (MCSE) for data management and analytics as well as the AWS Solution Architect associate certifications. Ian also writes for multiple technical blogs including SuperFunSQL.com which he founded in 2019.
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