DP-600T00-A Implementing Analytics Solutions Using Microsoft Fabric [Cloud Slice Provided]

1 - Ingest Data with Dataflows Gen2 in Microsoft Fabric

• Understand Dataflows (Gen2) in Microsoft Fabric
• Explore Dataflows (Gen2) in Microsoft Fabric
• Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric

2 - Ingest data with Spark and Microsoft Fabric notebooks

• Connect to data with Spark
• Write data into a lakehouse
• Consider uses for ingested data

3 - Use Data Factory pipelines in Microsoft Fabric

• Understand pipelines
• Use the Copy Data activity
• Use pipeline templates
• Run and monitor pipelines

4 - Get started with lakehouses in Microsoft Fabric

• Explore the Microsoft Fabric Lakehouse
• Work with Microsoft Fabric Lakehouses
• Explore and transform data in a lakehouse

5 - Organize a Fabric lakehouse using medallion architecture design

• Describe medallion architecture
• Implement a medallion architecture in Fabric
• Query and report on data in your Fabric lakehouse
• Considerations for managing your lakehouse

6 - Use Apache Spark in Microsoft Fabric

• 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

7 - Work with Delta Lake tables in Microsoft Fabric

• Understand Delta Lake
• Create delta tables
• Work with delta tables in Spark
• Use delta tables with streaming data

8 - Get started with data warehouses in Microsoft Fabric

• 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

9 - Load data into a Microsoft Fabric data warehouse

• Explore data load strategies
• Use data pipelines to load a warehouse
• Load data using T-SQL
• Load and transform data with Dataflow Gen2

10 - Query a data warehouse in Microsoft Fabric

• Use the SQL query editor
• Explore the visual query editor
• Use client tools to query a warehouse

11 - Monitor a Microsoft Fabric data warehouse

• Monitor capacity metrics
• Monitor current activity
• Monitor queries

12 - Understand scalability in Power BI

• Describe the significance of scalable models
• Implement Power BI data modeling best practices
• Configure large datasets

13 - Create Power BI model relationships

• Understand model relationships
• Set up relationships
• Use DAX relationship functions
• Understand relationship evaluation

14 - Use tools to optimize Power BI performance

• Use Performance analyzer
• Troubleshoot DAX performance by using DAX Studio
• Optimize a data model by using Best Practice Analyzer

15 - Enforce Power BI model security

• Restrict access to Power BI model data
• Restrict access to Power BI model objects
• Apply good modeling practices

Business users, IT professionals, data analysts, and anyone interested in building low-code applications, automating processes, and analyzing data using Microsoft Power Platform

Instructor-led sessions, course slides, sample datasets

Basic computer skills and familiarity with Microsoft Office or business applications

Microsoft Docs: Power Platform Fundamentals

This course prepares learners for the Microsoft PL-900: Power Platform Fundamentals Certification Exam. The exam evaluates knowledge of the Power Platform components, capabilities, and business applications. It includes multiple-choice and scenario-based questions to validate learners’ ability to implement basic solutions and leverage Power Platform tools effectively. Passing the exam demonstrates foundational proficiency in Microsoft Power Platform.

After this course, learners can pursue advanced Power Platform certifications, such as PL-200: Power Platform Functional Consultant, Power BI advanced courses, or Power Apps developer certifications.

Prerequisites

While there are no required prerequisites for taking this course, it is recommended that students have:
A foundational knowledge of core data concepts and how they’re implemented using Microsoft data services (see: Microsoft Azure AI Fundamentals Training (AI-900))
Experience designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value using Microsoft Power BI (see: Design and Manage Analytics Solutions Using Power BI (PL-300))