Microsoft Azure Data Engineering Training Course

Module 1: Introduction to Azure Data Engineering & DP-203

⏳ 2 hours

• Topics: Azure data services landscape, DP-203 exam objectives, course setup

• Hands-on: Provision a free-tier Azure account and run your first Data Factory pipeline

Module 2: Data Storage Solutions

⏳ 6 hours

• Topics: Data Lake Storage Gen2 architecture, Blob storage tiers, Synapse SQL pools

• Hands-on: Create storage accounts, ingest sample data, and query with serverless SQL

Module 3: Data Ingestion & Integration

⏳ 8 hours

• Topics: Azure Data Factory pipelines, mapping data flows, connectivity options

• Hands-on: Build and schedule ETL pipelines integrating multiple data sources

Module 4: Batch & Real-Time Processing

⏳ 6 hours

• Topics: Azure Databricks notebooks, Spark fundamentals, Delta Lake; Stream Analytics jobs and Event Hubs

• Hands-on: Develop a Spark job for data transformation and configure a streaming query

Module 5: Data Warehousing with Synapse

⏳ 6 hours

• Topics: Dedicated vs. serverless SQL pools, distribution strategies, workload management

• Hands-on: Design a star schema in Synapse and optimize query performance

Module 6: Security, Governance & Monitoring

⏳ 4 hours

• Topics: RBAC, managed identities, encryption at rest/in transit; Azure Monitor, Log Analytics

• Hands-on: Configure role assignments, set up diagnostic logs, and create alert rules

Module 7: Capstone Project & Exam Prep

⏳ 4 hours

• Topics: DP-203 exam blueprint review, sample questions, best-practice patterns

• Hands-on: Implement an end-to-end data solution—ingest, process, secure, and query—and walk through a practice exam

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