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Duration 21 hours
Course Outline
Foundations of End-to-End Analytics with Microsoft Fabric
- Briefing on the Microsoft Fabric platform
- Exploring the Lakehouse architectural model
- Visualizing the complete analytics workflow
Initiating Lakehouse Projects in Microsoft Fabric
- Examining the primary features and capabilities of Lakehouses
- Provisioning and setting up a new Lakehouse
- Populating Lakehouse tables with initial data
Harnessing Apache Spark within Microsoft Fabric
- Configuration steps for Apache Spark in Microsoft Fabric
- Applying Spark for large-scale distributed processing
- Executing data analysis and transformation via Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Core concepts of Delta Lake and Delta Tables
- Controlling data versions and integrity using Delta Tables
- Executing complex data transformations and queries
Handling Data Ingestion via Dataflows Gen2 in Microsoft Fabric
- Functional scope of Dataflows Gen2
- Architecting Dataflow solutions for efficient ingestion
- Embedding Dataflows into broader pipeline structures
Leveraging Data Factory Pipelines in Microsoft Fabric
- Overview of Data Factory pipeline capabilities
- Designing and coordinating automated data pipelines
- Automating data movement and transformation tasks
Requirements
- Familiarity with core data management fundamentals
- Practical experience working with SQL databases
- Foundational understanding of cloud computing principles
Target Learners
- Data engineers
- Database administrators
- Data analysts
