SQL: Build & Trace Pipelines

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

SQL: Build & Trace Pipelines

Coursera · Intermediate ·🔄 Data Engineering ·5mo ago

Key Takeaways

Builds and traces SQL pipelines for automated data processing and workflow automation

Original Description

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
AI explanation not available for this lesson yet
This lesson is still being prepared for the AI tutor. In the meantime, explore lessons that are ready.
Browse explainer-ready lessons →

Related Reads

📰
Excavating Legacy ETL: The AI Never Asserts a Fact It Could Look Up
Learn how to excavate legacy ETL using AI, focusing on data extraction and transformation without asserting facts that can be looked up
Dev.to AI
📰
Announcing Orchestra and n8n | The ultimate way to automate workflows
Learn to automate workflows with Orchestra and n8n, a powerful tool for data science and engineering
Medium · Data Science
📰
ELT is moving back to best-of-breed and Orchestration is the missing piece
Learn why ELT is shifting back to best-of-breed and how orchestration is the key missing piece, and why it matters for data engineering efficiency
Medium · Data Science
📰
Azure Data Engineer Course in Telugu: Build a Successful Data Engineering Career
Learn how to build a successful data engineering career with Azure Data Engineer Course in Telugu
Medium · DevOps
Up next
EY SAP Databricks: unlock real-time data and AI insights
EY Global
Watch →