Automate ETL Pipelines

Keeping location data up to date is critical, but manually updating databases every night does not scale. In this beginner-to-intermediate course (Python and SQL basics required), you will learn how to build, automate, and monitor a real-world geospatial ETL pipeline from start to finish. Through three progressive lessons, working through the practical scenario of nightly address updates, you will convert raw CSV data into spatial records using PostGIS, schedule reliable pipelines with Airflow, and analyze failures using logs and monitoring tools. Through short videos, hands-on learning, Coach-guided reflections, and scenario-based decision making, you will move beyond theory into applied data engineering. You are required to have basic Python skills, familiarity with CSV files, and introductory knowledge of databases and SQL. By the end of the course, you will have the confidence and skills to build production-ready geospatial pipelines that run automatically, recover from failures, and alert you when intervention is needed

• Build a complete geospatial ETL pipeline from raw data to spatial records
• Automate geospatial data updates using tools like Airflow
• Monitor and analyze pipeline failures using logs and monitoring tools
• Update spatial data automatically with accuracy and reliability
• Apply Python and SQL skills in a real-world engineering environment

• Basic knowledge of Python programming
• Familiarity with CSV files
• Introductory understanding of databases and SQL