Module 1: Explore Azure data services for modern analytics
- Describe the Azure data ecosystem for analytics
Module 2: Understand concepts of data analytics
- Describe types of data analytics
- Understand the data analytics process
Module 3: Explore data analytics at scale
- Explore data job roles in analytics
- Understand tools for scaling analytics solutions
Module 4: Introduction to Microsoft Purview
- Evaluate whether Microsoft Purview is appropriate for data discovery and governance needs
- Describe how the features of Microsoft Purview work to provide data discovery and governance
Module 5: Discover trusted data using Microsoft Purview
- Browse, search, and manage data catalog assets
- Use data catalog assets with Power BI
- Use Microsoft Purview in Azure Synapse
Module 6: Catalog data artifacts by using Microsoft Purview
- Describe asset classification in Microsoft Purview
Module 7: Manage Power BI assets by using Microsoft Purview
- Register and scan a Power BI tenant
- Use the search and browse functions to find data assets
- Describe the schema details and data lineage tracing of Power BI data assets
Module 8: Integrate Microsoft Purview and Azure Synapse Analytics
- Catalog Azure Synapse Analytics database assets in Microsoft Purview
- Configure Microsoft Purview integration in Azure Synapse Analytics
- Search the Microsoft Purview catalog from Synapse Studio
- Track data lineage in Azure Synapse Analytics pipelines activities
Module 9: Introduction to Azure Synapse Analytics
- Identify the business problems that Azure Synapse Analytics addresses
- Describe core capabilities of Azure Synapse Analytics
- Determine when to use Azure Synapse Analytics
Module 10: Use Azure Synapse serverless SQL pool to query files in a data lake
- Identify capabilities and use cases for serverless SQL pools in Azure Synapse Analytics
- Query CSV, JSON, and Parquet files using a serverless SQL pool
- Create external database objects in a serverless SQL pool
Module 11: Analyze data with Apache Spark in Azure Synapse Analytics
- Identify core features and capabilities of Apache Spark
- Configure a Spark pool in Azure Synapse Analytics
- Run code to load, analyze, and visualize data in a Spark notebook
Module 12: Analyze data in a relational data warehouse
- Design a schema for a relational data warehouse
- Create fact, dimension, and staging tables
- Use SQL to load data into data warehouse tables
- Use SQL to query relational data warehouse tables
Module 13: Choose a Power BI model framework
- Describe Power BI model fundamentals
- Determine when to develop an import model
- Determine when to develop a DirectQuery model
- Determine when to develop a composite model
- Choose an appropriate Power BI model framework
Module 14: Understand scalability in Power BI
- Describe the importance of building scalable data models
- Implement Power BI data modeling best practices
- Use the Power BI large dataset storage format
Module 15: Create and manage scalable Power BI dataflows
- Describe Power BI dataflows and use cases
- Describe best practices for implementing Power BI dataflows
- Create and consume Power BI dataflows
Module 16: Create Power BI model relationships
- Understand how model relationship work
- Set up relationships
- Use DAX relationship functions
- Understand relationship evaluation
Module 17: Use DAX time intelligence functions in Power BI Desktop models
- Define time intelligence
- Use common DAX time intelligence functions
- Create useful intelligence calculations
Module 18: Create calculation groups
- Explore how calculation groups work
- Maintain calculation groups in a model
- Use calculation groups in a Power BI report
Module 19: Enforce Power BI model security
- Restrict access to Power BI model data with RLS.
- Restrict access to Power BI model objects with OLS.
- Apply good development practices to enforce Power BI model security
Module 20: Use tools to optimize Power BI performance
- Optimize queries using performance analyzer
- Troubleshoot DAX performance using DAX Studio
- Optimize a data model using Tabular Editor
Module 21: Understand advanced data visualization concepts
- Create and import a custom report theme
- Create custom visuals with R or Python
- Enable personalized visuals in a report
- Review report performance using Performance Analyzer
- Design and configure Power BI reports for accessibility
Module 22: Monitor data in real-time with Power BI
- Describe Power BI real-time analytics
- Set up automatic page refresh
- Create real-time dashboards
- Set up auto-refresh paginated reports
Module 23: Create paginated reports
- Get data
- Create a paginated report
- Work with charts and tables on the report
- Publish the report
Module 24: Provide governance in a Power BI environment
- Define the key components of an effective BI governance model
- Describe the key elements associated with data governance
- Configure, deploy, and manage elements of a BI governance strategy
- Set up BI help and support settings
Module 25: Facilitate collaboration and sharing in Power BI
- Understand the differences between My workspace, workspaces, and apps
- Describe new workspace capabilities and how they improve the user experience
- Anticipate migration impact to Power BI users
- Share, publish to the web, embed links and secure Power BI reports, dashboards, and content
Module 26: Monitor and audit usage
- Discover what usage metrics are available through the Power BI admin portal
- Optimize use of usage metrics for dashboards and reports
- Distinguish between audit logs and the activity logs
Module 27: Provision Premium capacity in Power BI
- Describe the difference between Power BI Pro and Power BI Premium
- Define dataset eviction
- Explain how Power BI manages memory resources
- List three external tools you can use with Power BI Premium
Module 28: Establish a data access infrastructure in Power BI
- Understand the difference between gateways, the various connectivity modes, and data refresh methods
- Describe the gateway network requirements, where to place the gateway in your network, and how to use clustering to ensure high availability
- Scale, monitor, and manage gateway performance and users
Module 29: Broaden the reach of Power BI
- Describe the various embedding scenarios that allow you to broaden the reach of Power BI
- Understand the options for developers to customize Power BI solutions
- Learn to provision and optimize Power BI embedded capacity and create and deploy dataflows
- Build custom Power BI solutions template apps
Module 30: Automate Power BI administration
- Use REST APIs to automate common Power BI admin tasks
- Apply Power BI Cmdlets for Windows PowerShell and PowerShell core
- Use Power BI Cmdlets
- Automate common Power BI admin tasks with scripting
Module 31: Build reports using Power BI within Azure Synapse Analytics
- Describe the Power BI and Synapse workspace integration
- Understand Power BI data sources
- Describe optimization options
- Visualize data with serverless SQL pools
Module 32: Design a Power BI application lifecycle management strategy
- Outline the application lifecycle process
- Choose a source control strategy
- Design a deployment strategy
Module 33: Create and manage a Power BI deployment pipeline
- Articulate the benefits of deployment pipelines
- Create a deployment pipeline using Premium workspaces
- Assign and deploy content to pipeline stages
- Describe the purpose of deployment rules
- Deploy content from one pipeline stage to another
Module 34: Create and manage Power BI assets
- Create specialized datasets
- Create live and DirectQuery connections
- Use Power BI service lineage view
- Use XMLA endpoint to connect datasets
