Microsoft Fabric Analytics Engineer Training (DP 600)

DP-600 is designed for data professionals who want to build and manage analytics solutions using Microsoft Fabric. The course focuses on integrating data engineering, data warehousing, and real-time analytics using a unified SaaS platform.

This course provides hands-on experience in Microsoft Fabric, including OneLake, Data Factory, Synapse Data Engineering, Real-Time Analytics, and Power BI.

Participants will learn how to ingest, transform, model, and visualize data using a single unified analytics platform.

Module 1: Introduction to Microsoft Fabric

Topics Covered:

• Microsoft Fabric overview
• SaaS-based analytics platform
• OneLake architecture

Lab:

• Create Microsoft Fabric workspace
• Explore OneLake storage
• Navigate Fabric components

Outcome:
Understand Fabric ecosystem and architecture.

Module 2: Data Ingestion and Data Factory in Fabric

Topics Covered:

• Data ingestion strategies
• Data pipelines in Fabric
• Data Factory concepts

Lab:

• Create data pipeline in Fabric
• Ingest data from external sources
• Schedule data flows

Outcome:
Build automated data ingestion pipelines.

Module 3: Data Engineering in Fabric (Spark)

Topics Covered:

• Lakehouse architecture
• Apache Spark in Fabric
• Data transformation

Lab:

• Create Lakehouse
• Run Spark notebooks
• Transform and clean datasets

Outcome:
Process and transform large-scale data.

Module 4: Data Warehouse in Fabric

Topics Covered:

• Fabric Data Warehouse
• SQL-based analytics
• Data modeling

Lab:

• Create Fabric data warehouse
• Load structured data
• Run SQL analytics queries

Outcome:
Build scalable cloud data warehouses.

Module 5: Real-Time Analytics

Topics Covered:

• Streaming data concepts
• Event processing
• KQL (Kusto Query Language)

Lab:

• Ingest streaming data
• Query real-time data using KQL
• Build real-time dashboard

Outcome:
Analyze real-time business data.

Module 6: Data Modeling and Semantic Models

Topics Covered:

• Star schema design
• Semantic models in Power BI
• Data relationships

Lab:

• Build semantic model
• Define relationships
• Optimize data model for reporting

Outcome:
Create efficient analytics models.

Module 7: Power BI Integration in Fabric

Topics Covered:

• Power BI integration
• Report building
• Data visualization

Lab:

• Build Power BI report from Fabric data
• Create dashboards
• Publish reports

Outcome:
Deliver business insights using visualization.

Module 8: Security, Governance, and Monitoring

Topics Covered:

• Data governance in Fabric
• Security roles and permissions
• Monitoring and optimization

Lab:

• Configure workspace security
• Monitor data pipelines
• Apply governance policies

Outcome:
Secure and manage analytics environment.