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Course Outline
Introduction to End-to-End Analytics in Microsoft Fabric
- Overview of the Microsoft Fabric platform
- Exploring Lakehouse Architecture
- End-to-End Analytics Workflows
Initializing Lakehouses in Microsoft Fabric
- Key features and capabilities of Lakehouses
- Creation and configuration of a Lakehouse
- Populating Lakehouse tables with data
Integrating Apache Spark with Microsoft Fabric
- Setup of Apache Spark within Microsoft Fabric
- Harnessing Spark for distributed data processing
- Data analysis and transformation via Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Overview of Delta Lake and Delta tables
- Data versioning and management through Delta tables
- Executing data transformations and queries
Data Ingestion via Dataflows Gen2 in Microsoft Fabric
- Features of Dataflows Gen2
- Architecting data ingestion solutions with Dataflows
- Embedding Dataflows into broader data pipelines
Leveraging Data Factory Pipelines in Microsoft Fabric
- Introduction to Data Factory Pipelines
- Construction and orchestration of data pipelines
- Automation of data movement and transformation tasks
Requirements
- Familiarity with core data management principles
- Practical experience with SQL databases
- Fundamental understanding of cloud computing concepts
Intended Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
