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Course Outline
Introduction to End-to-End Analysis with Microsoft Fabric
- High-level view of the Microsoft Fabric ecosystem.
- Exploring the Lakehouse architectural model.
- Mapping out the full analytics workflow.
Initiating Lakehouse Operations in Microsoft Fabric
- Key features and technical capabilities of Lakehouses.
- Steps for creating and configuring a Lakehouse instance.
- Methods for ingesting data into Lakehouse tables.
Integrating Apache Spark within Microsoft Fabric
- Setup and configuration of Apache Spark in Fabric.
- Harnessing Spark for large-scale distributed data processing.
- Data analysis and transformation using Spark DataFrames.
Managing Delta Lake Tables in Microsoft Fabric
- Overview of Delta Lake technology and table structures.
- Data versioning and lifecycle management via Delta Tables.
- Executing data transformations and complex queries.
Data Ingestion Strategies with Dataflows Gen2
- Technical scope and capabilities of Dataflows Gen2.
- Architecting Dataflow solutions for efficient ingestion.
- Seamless integration of Dataflows into broader pipelines.
Orchestrating Pipelines with Data Factory
- Functional overview of Data Factory pipelines.
- Construction and coordination of data pipeline flows.
- Automation of data movement and transformation processes.
Requirements
- Familiarity with core data management principles.
- Proficiency in working with SQL databases.
- Foundational knowledge of cloud computing paradigms.
Target Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
