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Course Outline
Introduction to Comprehensive Analysis with Microsoft Fabric
- Microsoft Fabric: A High-Level Overview
- Exploring the Lakehouse Architectural Model
- The End-to-End Analytics Lifecycle
Initiating Lakehouse Operations in Microsoft Fabric
- Key Features and Functionalities of Lakehouses
- Provisioning and Setup of a Lakehouse
- Loading Data into Lakehouse Tables
Integrating Apache Spark in Microsoft Fabric
- Setup and Configuration of Apache Spark
- Harnessing Spark for Scalable Data Processing
- Data Analysis and Transformation via Spark DataFrames
Managing Delta Lake Tables in Microsoft Fabric
- Fundamentals of Delta Lake and Delta Tables
- Data Versioning and Governance with Delta Tables
- Executing Data Transformations and Complex Queries
Data Ingestion Strategies with Dataflows Gen2
- Core Capabilities of Dataflows Gen2
- Architecting Dataflow Solutions for Ingestion
- Embedding Dataflows within Broader Data Pipelines
Orchestrating Pipelines with Data Factory
- Overview of Data Factory Pipeline Architecture
- Construction and Orchestration of Data Flows
- Automation of Data Movement and Transformation Tasks
Requirements
- Familiarity with core data management principles
- Practical experience working with SQL databases
- Fundamental understanding of cloud computing paradigms
Intended Audience
- Data engineers
- Database administrators
- Data analysts
21 Hours
