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Course Outline
Foundations of End-to-End Analytics in Microsoft Fabric
- Broad overview of Microsoft Fabric
- Exploring the Lakehouse Architecture
- The complete analytics workflow from start to finish
Initiating Lakehouse Projects in Microsoft Fabric
- Key features and functional capabilities of Lakehouses
- Steps to create and configure a Lakehouse instance
- Importing data into Lakehouse tables
Integrating Apache Spark with Microsoft Fabric
- Configuration of Apache Spark within the Microsoft Fabric environment
- Harnessing Spark for large-scale, distributed data processing
- Data analysis and transformation using Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Introduction to Delta Lake and the Delta Table format
- Data versioning and management strategies with Delta Tables
- Executing data transformations and running queries
Data Ingestion via Dataflows Gen2 in Microsoft Fabric
- Feature set and capabilities of Dataflows Gen2
- Architecting Dataflow solutions for efficient data ingestion
- Seamless integration of Dataflows into broader data pipelines
Leveraging Data Factory Pipelines in Microsoft Fabric
- Core concepts of Data Factory Pipelines
- Construction and orchestration of data workflows
- 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
Target Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
