SQL: Build & Trace Pipelines
Did you know that even small inefficiencies or errors in SQL pipelines can cascade across an entire data warehouse, impacting dashboards, models, and business decisions? Mastering SQL-based workflow automation and traceability is essential for reliable data operations. This Short Course was created to help data engineering professionals build automated data processing workflows and systematically analyze pipeline dependencies for enterprise data infrastructure. By completing this course, you will be able to write parameterized SQL for scheduled ELT jobs and trace multi-step SQL pipelines to understand data flow, transformation logic, and upstream-downstream relationships—skills that strengthen both accuracy and maintainability in production systems. By the end of this 4-hour long course, you will be able to: Apply parameterized SQL to create scheduled ELT jobs for data processing. Analyze a multi-step SQL pipeline to trace data flow and transformation logic. This course is unique because it combines automation, traceability, and SQL craftsmanship, giving you the tools to build scalable pipelines while developing deep insight into how data moves and transforms across complex enterprise systems. To be successful in this project, you should have: Advanced SQL skills Data warehousing knowledge Basic ETL concepts Familiarity with scheduling tools
