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Exam Code: DP-500
Exam Name: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI
Exam Q&As: 160 Q&As
Last update: May 24, 2024

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Introduce Microsoft DP-500 Exam

The Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI DP-500 exam is the part of the requirements for Microsoft Certified: Azure Enterprise Data Analyst Associate certification. Candidates for the DP-500 exam should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions. The Microsoft DP-500 exam is available in multiple languages, including English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Chinese (Traditional), Italian. Make sure that you can pass the DP-500 exam and earn the Microsoft Certified: Azure Enterprise Data Analyst Associate certification to promote your positions.

Learning DP-500 Exam Objectives Is Strongly Recommended

  • Manage Power BI assets by using Microsoft Purview
  • Identify data sources in Azure by using Microsoft Purview
  • Recommend settings in the Power BI admin portal
  • Recommend a monitoring and auditing solution for a data analytics environment, including Power BI REST API and PowerShell cmdlets
  • Identify requirements for a solution, including features, performance, and licensing strategy
  • Configure and manage Power BI capacity
  • Recommend and configure an on-premises gateway in Power BI
  • Recommend and configure a Power BI tenant or workspace to integrate with Azure Data Lake Storage Gen2
  • Integrate an existing Power BI workspace into Azure Synapse Analytics
  • Commit code and artifacts to a source control repository in Azure Synapse Analytics
  • Recommend a deployment strategy for Power BI assets
  • Recommend a source control strategy for Power BI assets
  • Implement and manage deployment pipelines in Power BI
  • Perform impact analysis of downstream dependencies from dataflows and datasets
  • Recommend automation solutions for the analytics development lifecycle, including Power BI REST API and PowerShell cmdlets
  • Deploy and manage datasets by using the XMLA endpoint
  • Create reusable assets, including Power BI templates, Power BI data source (.pbids) files, and shared datasets
  • Identify an appropriate Azure Synapse pool when analyzing data
  • Recommend appropriate file types for querying serverless SQL pools
  • Query relational data sources in dedicated or serverless SQL pools, including querying partitioned data sources
  • Use a machine learning PREDICT function in a query
  • Identify data loading performance bottlenecks in Power Query or data sources
  • Implement performance improvements in Power Query and data sources
  • Create and manage scalable Power BI dataflows
  • Identify and manage privacy settings on data sources
  • Create queries, functions, and parameters by using the Power Query Advanced Editor
  • Query advanced data sources, including JSON, Parquet, APIs, and Azure Machine Learning models
  • Choose when to use DirectQuery for Power BI datasets
  • Choose when to use external tools, including DAX Studio and Tabular Editor 2
  • Create calculation groups
  • Write calculations that use DAX variables and functions, for example handling blanks or errors, creating virtual relationships, and working with iterators
  • Design and build a large format dataset
  • Design and build composite models, including aggregations
  • Design and implement enterprise-scale row-level security and object-level security
  • Identify and implement performance improvements in queries and report visuals
  • Troubleshoot DAX performance by using DAX Studio
  • Optimize a data model by using Tabular Editor 2
  • Analyze data model efficiency by using VertiPaq Analyzer
  • Implement incremental refresh (including the use of query folding)
  • Optimize a data model by using denormalization
  • Explore data by using native visuals in Spark notebooks
  • Explore and visualize data by using the Azure Synapse SQL results pane
  • Create and import a custom report theme
  • Create R or Python visuals in Power BI
  • Connect to and query datasets by using the XMLA endpoint
  • Design and configure Power BI reports for accessibility
  • Enable personalized visuals in a report
  • Configure automatic page refresh
  • Create and distribute paginated reports in Power BI Report Builder

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