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Course Outline
Introduction to Holistic Analytics with Microsoft Fabric
- High-level view of Microsoft Fabric
- Exploring the Lakehouse structural design
- End-to-end analytics processes
Initiating Lakehouse Operations in Microsoft Fabric
- Key features and functionalities of Lakehouses
- Creation and setup of a Lakehouse instance
- Populating Lakehouse tables with incoming data
Integrating Apache Spark into Microsoft Fabric
- Setting up Apache Spark within the Fabric ecosystem
- Harnessing Spark for distributed data handling
- Performing analysis and data reshaping via Spark DataFrames
Managing Delta Lake Tables within Microsoft Fabric
- Basics of Delta Lake and Delta table structures
- Handling data versioning and management with Delta Tables
- Executing data transformations and query operations
Data Ingestion Strategies with Dataflows Gen2 in Microsoft Fabric
- Feature set and capabilities of Dataflows Gen2
- Architecting dataflow solutions for efficient ingestion
- Connecting Dataflows to broader data pipeline systems
Leveraging Data Factory Pipelines in Microsoft Fabric
- Overview of Data Factory pipeline capabilities
- Constructing and orchestrating pipeline workflows
- Automating data transfers and transformation tasks
Requirements
- Familiarity with core data management methodologies
- Practical experience working with SQL databases
- Fundamental grasp of cloud computing principles
Target Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
