Data Engineering
Data Engineering — Practitioner
Industrialize your data flows with Azure Data Factory and a cloud Data Warehouse.
You build ETL and ELT pipelines feeding a Data Warehouse on Azure, orchestrated with Data Factory. The capstone is an end-to-end cloud pipeline, from source to an analysis-ready model.
Objectives
- Design robust ETL and ELT pipelines
- Feed a structured Data Warehouse
- Orchestrate flows with Azure Data Factory
- Monitor and stabilize scheduled processing
Program
ETL and ELT
- Comparing ETL and ELT approaches
- Transformations and staging
- Handling incremental loads
Data Warehouse
- Dimensional modeling
- Loading facts and dimensions
- Query optimization
Azure Data Factory
- Pipelines, activities and triggers
- Connections to cloud and on-premises sources
- End-to-end cloud pipeline
Prerequisites
Solid SQL and Python foundations.