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Microsoft DP-500 Exam Topics

Microsoft DP-500 Exam

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

Total Questions: 162

What is Included in the Microsoft DP-500 Exam?

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Microsoft DP-500 Exam Overview :

Exam Name Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI
Exam Code DP-500
Exam Registration Price $165
Official Information https://docs.microsoft.com/en-us/learn/certifications/exams/dp-500
See Expected Questions Microsoft DP-500 Expected Questions in Actual Exam
Take Self-Assessment Use Microsoft DP-500 Practice Test to Assess your preparation - Save Time and Reduce Chances of Failure

Microsoft DP-500 Exam Topics :

Section Weight Objectives
Implement and manage a data analytics environment 25–30% Govern and administer a data analytics environment
  •  manage Power BI assets by using Azure Purview
  •  identify data sources in Azure by using Azure 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

Integrate an analytics platform into an existing IT infrastructure
  •  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

Manage the analytics development lifecycle
  •  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
Query and transform data 20–25% Query data by using Azure Synapse Analytics
  •  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

Ingest and transform data by using Power BI
  •  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
Implement and manage data models 25–30% Design and build tabular 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

Optimize enterprise-scale data models
  •  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
  •  optimize a data model by using denormalization
Explore and visualize data 20–25% Explore data by using Azure Synapse Analytics
  •  explore data by using native visuals in Spark notebooks
  •  explore and visualize data by using the Azure Synapse SQL results pane

Visualize data by using Power BI
  •  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

Updates in the Microsoft DP-500 Exam Topics:

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