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Course Outline
Introduction to End-to-End Analytics with Microsoft Fabric
- Overview of the Microsoft Fabric ecosystem
- Comprehending the Lakehouse Architecture
- The End-to-End Analytics Workflow
Initiating Lakehouse Operations in Microsoft Fabric
- Key Features and Capabilities of Lakehouses
- Provisioning and Configuring a Lakehouse
- Populating Lakehouse Tables with Data
Integrating Apache Spark within Microsoft Fabric
- Setup and Configuration of Apache Spark
- Harnessing Spark for Distributed Data Processing
- Data Analysis and Transformation via Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Basics of Delta Lake and Delta Tables
- Controlling and Versioning Data with Delta Tables
- Executing Data Transformations and Queries
Enhancing Data Ingestion with Dataflows Gen2
- Core Capabilities of Dataflows Gen2
- Architecting Dataflow Solutions for Ingestion
- Integrating Dataflows into Broader Data Pipelines
Leveraging Data Factory Pipelines in Microsoft Fabric
- Foundations of Data Factory Pipelines
- Construction and Orchestration of Data Pipelines
- Automation of Data Movement and Transformation Tasks
Requirements
- Familiarity with core data management principles
- Practical experience with SQL databases
- Foundational understanding of cloud computing concepts
Target Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
