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Course Outline
Foundations of End-to-End Analytics with Microsoft Fabric
- Overview of the Microsoft Fabric platform
- Exploring the Lakehouse architectural design
- The complete analytics workflow from start to finish
Initiating Lakehouse Development in Microsoft Fabric
- Key features and functional capabilities of Lakehouses
- Steps to create and configure a new Lakehouse
- Methods for loading data into Lakehouse tables
Integrating Apache Spark within Microsoft Fabric
- Setup and configuration of Apache Spark in Fabric
- Utilizing Spark for distributed data processing tasks
- Data analysis and transformation using Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Introduction to the Delta Lake framework and table structures
- Techniques for data versioning and management via Delta Tables
- Executing data transformations and complex queries
Data Ingestion Strategies with Dataflows Gen2 in Microsoft Fabric
- Exploring the capabilities of Dataflows Gen2
- Architecting dataflow solutions for efficient ingestion
- Connecting Dataflows to broader data pipelines
Leveraging Data Factory Pipelines in Microsoft Fabric
- Introduction to Data Factory pipeline functionality
- Construction and orchestration of data pipelines
- Automation of data movement and transformation processes
Requirements
- Familiarity with core data management principles
- Practical experience with SQL databases
- Foundational understanding of cloud computing concepts
Intended Participants
- Data engineers
- Database administrators
- Data analysts
21 Hours
