Duration:

4 Days

Audience:

Employees of federal, state and local governments; and businesses working with the government.

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.

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.

Course 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.

Course Outline

1 – Introduction to end-to-end analytics using Microsoft Fabric

  • Explore end-to-end analytics with Microsoft Fabric
  • Data teams and Microsoft Fabric
  • Enable and use Microsoft Fabric

2 – Get started with lakehouses in Microsoft Fabric

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

3 – 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

4 – 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

5 – Use Data Factory pipelines in Microsoft Fabric

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

6 – 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

7 – 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

8 – Get started with Real-Time Intelligence in Microsoft Fabric

  • Describe Microsoft Fabric Real-Time Intelligence?
  • Understand KQL database and tables
  • Describe Microsoft Fabric Real-Time hub
  • Write queries with KQL

9 – Get started with data science in Microsoft Fabric

  • Understand the data science process
  • Explore and process data with Microsoft Fabric
  • Train and score models with Microsoft Fabric

10 – Get started with Data Activator in Microsoft Fabric

  • Understand Data Activator
  • Get started with Data Activator
  • Understand triggers, conditions and actions in Data Activator
  • Get data from Power BI Reports and EventStreams with Data Activator
  • Assign data in Data Activator
  • Create triggers in Data Activator

11 – Administer Microsoft Fabric

  • Understand the Fabric Architecture
  • Understand the Fabric administrator role
  • Manage Fabric security
  • Govern data in Fabric

12 – Introduction to end-to-end analytics using Microsoft Fabric

  • Explore end-to-end analytics with Microsoft Fabric
  • Data teams and Microsoft Fabric
  • Enable and use Microsoft Fabric

13 – Get started with lakehouses in Microsoft Fabric

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

14 – 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

15 – 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

16 – 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

17 – Use Data Factory pipelines in Microsoft Fabric

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

18 – 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

19 – 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

20 – Ingest data with Spark and Microsoft Fabric notebooks

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

21 – Use Data Factory pipelines in Microsoft Fabric

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

22 – 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

23 – 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

24 – Query a data warehouse in Microsoft Fabric

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

25 – Monitor a Microsoft Fabric data warehouse

  • Monitor capacity metrics
  • Monitor current activity
  • Monitor queries

26 – Understand scalability in Power BI

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

27 – Create Power BI model relationships

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

28 – 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

29 – Enforce Power BI model security

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