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Course Outline
Foundations of End-to-End Analytics with Microsoft Fabric
- High-level overview of the Microsoft Fabric platform
- Analyzing the underlying Lakehouse architecture
- Mappings of end-to-end analytics workflows
Initiating Lakehouse Operations in Microsoft Fabric
- Exploring core functionalities and capabilities of Lakehouses
- Steps for creating and configuring a new Lakehouse
- Methods for ingesting data into Lakehouse tables
Integrating Apache Spark within Microsoft Fabric
- Setup and configuration of Apache Spark in the Fabric environment
- Harnessing Spark for scalable distributed data processing
- Executing data analysis and transformation tasks via Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Basic concepts of Delta Lake and Delta Tables
- Strategies for managing data and maintaining version history with Delta Tables
- Executing data transformations and running queries
Streamlining Data Ingestion via Dataflows Gen2
- Key capabilities offered by Dataflows Gen2
- Architecting dataflow solutions focused on ingestion
- Seamless integration of dataflows into broader data pipelines
Leveraging Data Factory Pipelines in Microsoft Fabric
- General overview of Data Factory pipeline mechanisms
- Constructing and orchestrating complex data pipelines
- Automation of data movement and transformation processes
Requirements
- Familiarity with fundamental data management concepts
- Practical experience working with SQL databases
- Foundational understanding of cloud computing principles
Target Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
