Azure Data Project-Oriented Training
Azure Data Project-Oriented Training
Audience: Intermediate data engineers / analysts
Focus: End-to-end data project – problem statement → KPI → data cleaning → semantic model → report
Session | Topic | Objectives / Outcomes | Hands-On / Deliverable |
1 | Project Kickoff & Environment Setup | – Understand project goals and KPIs – Set up Microsoft Fabric workspace | – Provision workspace & Lakehouse – Document project charter with KPIs |
2 | Data Ingestion & Exploration | – Ingest raw data – Explore datasets using PySpark & SQL | – Build ingestion pipeline – EDA notebook (data dictionary, missing values, distributions) |
3 | Data Cleaning & Transformation | – Clean and transform data – Apply business logic using SQL/PySpark | – Transformation pipeline – Cleaned dataset in Lakehouse |
4 | Semantic Modeling | – Build semantic model for reporting – Calculate KPIs | – Create model with key tables & measures – KPI summary table |
5 | Report Development | – Build reports/dashboards based on business requirements | – Power BI report or Fabric dashboard – Validate against KPIs |
6 | Deployment & Knowledge Transfer | – Deploy solution – Review & document process | – Production-ready solution – Final documentation & architecture diagram |
Tools & Technologies:
Microsoft Fabric: Lakehouse, Pipelines, Notebooks, Semantic Models
Languages: PySpark, SQL
Visualization: Power BI