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Microsoft Fabric Analytics Engineer

Price
2,380 USD
4
MOC-DP-600T00
Classroom Training, Online Training
Microsoft

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  • Guaranteed to Run
    Date: 3-Dec-2024 to 6-Dec-2024
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: united
    Price: 2,380 USD
  • Date: 3-Feb-2025 to 6-Feb-2025
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 2,380 USD
  • Date: 17-Mar-2025 to 20-Mar-2025
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 2,380 USD
  • Date: 28-Apr-2025 to 1-May-2025
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 2,380 USD
  • Date: 9-Jun-2025 to 12-Jun-2025
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 2,380 USD
  • Date: 21-Jul-2025 to 24-Jul-2025
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 2,380 USD
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Course Description

Overview

This course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will build on existing analytics experience and will learn how to use Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy analytics assets.

This course is best suited for those who have the PL-300 certification or similar expertise in using Power BI for data transformation, modeling, visualization, and sharing. Also, learners should have prior experience in building and deploying data analytics solutions at the enterprise level.
 

Objectives


 

Audience

The primary audience for this course is data professionals with experience in data modeling, extraction, and analytics. DP-600 is designed for professionals who want to use Microsoft Fabric to create and deploy enterprise-scale data analytics solutions.
 

Prerequisites


     

Topics

Ingest Data with Dataflows Gen2 in Microsoft Fabric
  • Introduction
  • Understand Dataflows Gen2 in Microsoft Fabric
  • Explore Dataflows Gen2 in Microsoft Fabric
  • Integrate Dataflows Gen2 and Pipelines in Microsoft Fabric
  • Exercise - Create and use a Dataflow Gen2 in Microsoft Fabric
  • Knowledge check
Ingest data with Spark and Microsoft Fabric notebooks
  • Introduction
  • Connect to data with Spark
  • Write data into a lakehouse
  • Consider uses for ingested data
  • Exercise - Ingest data with Spark and Microsoft Fabric notebooks
  • Knowledge check
Use Data Factory pipelines in Microsoft Fabric
  • Introduction
  • Understand pipelines
  • Use the Copy Data activity
  • Use pipeline templates
  • Run and monitor pipelines
  • Exercise - Ingest data with a pipeline
  • Knowledge check
Get started with lakehouses in Microsoft Fabric
  • Introduction
  • Explore the Microsoft Fabric Lakehouse
  • Work with Microsoft Fabric Lakehouses
  • Explore and transform data in a lakehouse
  • Exercise - Create and ingest data with a Microsoft Fabric Lakehouse
  • Knowledge check
Organize a Fabric lakehouse using medallion architecture design
  • Introduction
  • Describe medallion architecture
  • Implement a medallion architecture in Fabric
  • Query and report on data in your Fabric lakehouse
  • Considerations for managing your lakehouse
  • Exercise - Organize your Fabric lakehouse using a medallion architecture
  • Knowledge check
Use Apache Spark in Microsoft Fabric
  • Introduction
  • Prepare to use Apache Spark
  • Run Spark code
  • Work with data in a Spark dataframe
  • Work with data using Spark SQL
  • Visualize data in a Spark notebook
  • Exercise - Analyze data with Apache Spark
  • Knowledge check
Work with Delta Lake tables in Microsoft Fabric
  • Introduction
  • Understand Delta Lake
  • Create delta tables
  • Work with delta tables in Spark
  • Use delta tables with streaming data
  • Exercise - Use delta tables in Apache Spark
  • Knowledge check
Get started with data warehouses in Microsoft Fabric
  • Introduction
  • Understand data warehouse fundamentals
  • Understand data warehouses in Fabric
  • Query and transform data
  • Prepare data for analysis and reporting
  • Secure and monitor your data warehouse
  • Exercise - Analyze data in a data warehouse
  • Knowledge check
Load data into a Microsoft Fabric data warehouse
  • Introduction
  • Explore data load strategies
  • Use data pipelines to load a warehouse
  • Load data using T-SQL
  • Load and transform data with Dataflow Gen2
  • Exercise: Load data into a warehouse in Microsoft Fabric
  • Knowledge check
Query a data warehouse in Microsoft Fabric
  • Introduction
  • Use the SQL query editor
  • Explore the visual query editor
  • Use client tools to query a warehouse
  • Exercise: Query a data warehouse in Microsoft Fabric
  • Knowledge check
Monitor a Microsoft Fabric data warehouse
  • Introduction
  • Monitor capacity metrics
  • Monitor current activity
  • Monitor queries
  • Exercise - Monitor a data warehouse in Microsoft Fabric
  • Knowledge check
Understand scalability in Power BI
  • Introduction
  • Describe the significance of scalable models
  • Implement Power BI data modeling best practices
  • Configure large datasets
  • Exercise: Create a star schema model
  • Knowledge check
Create Power BI model relationships
  • Introduction
  • Understand model relationships
  • Set up relationships
  • Use DAX relationship functions
  • Understand relationship evaluation
  • Exercise: Work with model relationships
  • Knowledge check
Use tools to optimize Power BI performance
  • Introduction
  • Use Performance analyzer
  • Troubleshoot DAX performance by using DAX Studio
  • Optimize a data model by using Best Practice Analyzer
  • Exercise: Use tools to optimize Power BI performance
  • Knowledge check
Enforce Power BI model security
  • Introduction
  • Restrict access to Power BI model data
  • Restrict access to Power BI model objects
  • Apply good modeling practices
  • Exercise: Enforce model security
  • Knowledge check
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