DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI

• Describe the Azure data ecosystem for analytics

• Describe types of data analytics
• Understand the data analytics process

• Explore data job roles in analytics
• Understand tools for scaling analytics solutions

• 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.

• Browse, search, and manage data catalog assets.
• Use data catalog assets with Power BI.
• Use Microsoft Purview in Azure Synapse Studio.

• Describe asset classification in 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.

• 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.

• Identify the business problems that Azure Synapse Analytics addresses.
• Describe core capabilities of Azure Synapse Analytics.
• Determine when to use Azure Synapse Analytics.

• 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

• 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.

• 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.

• 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.

• Describe Power BI dataflows and use cases.
• Describe best practices for implementing Power BI dataflows.
• Create and consume Power BI dataflows.

• Understand how model relationship work.
• Set up relationships.
• Use DAX relationship functions.
• Understand relationship evaluation.

• Define time intelligence.
• Use common DAX time intelligence functions.
• Create useful intelligence calculations.

• Explore how calculation groups work.
• Maintain calculation groups in a model.
• Use calculation groups in a Power BI report.

• Explore how calculation groups work.
• Maintain calculation groups in a model.
• Use calculation groups in a Power BI report.

• 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.

• Optimize queries using performance analyzer.
• Troubleshoot DAX performance using DAX Studio.
• Optimize a data model using Tabular Editor.

• 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.

• Describe Power BI real-time analytics.
• Set up automatic page refresh.
• Create real-time dashboards.
• Set up auto-refresh paginated reports.

• Get data.
• Create a paginated report.
• Work with charts and tables on the report.
• Publish the report.

• 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

• 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

• 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

• 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.

• 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

• 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

• Describe the Power BI and Synapse workspace integration
• Understand Power BI data sources
• Describe optimization options
• Visualize data with serverless SQL pools

• Outline the application lifecycle process.
• Choose a source control strategy.
• Design a deployment strategy.

• 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

• Create specialized datasets.
• Create live and DirectQuery connections.
• Use Power BI service lineage view.
• Use XMLA endpoint to connect datasets.

4 days