Exam: DP-500
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Exam DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions
Using Microsoft Azure and Microsoft Power BI
Languages: English, Japanese, Chinese (Simplified), Korean, German, French,
Spanish, Portuguese (Brazil), Russian, Arabic (Saudi Arabia), Chinese
(Traditional), Italian, Indonesian (Indonesia)
Retirement date: none
This exam measures your ability to accomplish the following technical tasks:
implement and manage a data analytics environment; query and transform data;
implement and manage data models; and explore and visualize data.
Skills measured
The English language version of this exam will be updated on February 6,
2023. Review the study guide linked in the preceding 'Tip' box for details about
the skills measured and upcoming changes.
Implement and manage a data analytics environment (25-30%)
Query and transform data (20-25%)
Implement and manage data models (25-30%)
Explore and visualize data (20-25%)
Audience profile
Candidates for the Azure Enterprise Data Analyst Associate certification should
have subject matter expertise in designing, creating, and deploying
enterprise-scale data analytics solutions.
Responsibilities for this role include performing advanced data analytics at
scale, such as cleaning and transforming data, designing, and building
enterprise data models, incorporating advanced analytics capabilities,
integrating with IT infrastructure, and applying development lifecycle
practices. These professionals help collect enterprise-level requirements for
data analytics solutions that include Azure and Power BI. They also advise on
data governance and configuration settings for Power BI administration, monitor
data usage, and optimize performance of the data analytics solutions.
Azure enterprise data analysts collaborate with other roles, such as solution
architects, data engineers, data scientists, AI engineers, database
administrators, and Power BI data analysts.
Candidates for this exam should have advanced Power BI skills, including
managing data repositories and data processing in the cloud and on-premises,
along with using Power Query and Data Analysis Expressions (DAX). They should
also be proficient in consuming data from Azure Synapse Analytics and should
have experience querying relational databases, analyzing data by using
Transact-SQL (T-SQL), and visualizing data.
* Implement and manage a data analytics environment (25-30%)
* Query and transform data (20-25%)
* Implement and manage data models (25-30%)
* Explore and visualize data (20-25%)
Implement and manage a data analytics environment (25-30%)
Govern and administer a data analytics environment
* 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
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 (including the use of query folding)
* 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
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QUESTION 1
What should you configure in the deployment pipeline?
A. a backward deployment
B. a selective deployment
C. auto-binding
D. a data source rule
Answer: D
QUESTION 2
You need to configure the Sales Analytics workspace to meet the ad hoc
reporting requirements.
What should you do?
A. Grant the sales managers the Build permission for the existing Power Bl
datasets.
B. Grant the sales managers admin access to the existing Power Bl workspace.
C. Create a deployment pipeline and grant the sales managers access to the
pipeline.
D. Create a PBIT file and distribute the file to the sales managers.
Answer: D
QUESTION 3
You need to recommend a solution to ensure that sensitivity labels are
applied. The solution must minimize administrative effort.
Which three actions should you include in the recommendation? Each correct
answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. From the Power Bl Admin portal, set Allow users to apply sensitivity labels
for Power Bl content to Enabled.
B. From the Power Bl Admin portal, set Apply sensitivity labels from data
sources to their data in Power Bl to Enabled.
C. In SQLDW. apply sensitivity labels to the columns in the Customer and
CustomersWithProductScore tables.
D. In the Power Bl datasets, apply sensitivity labels to the columns in the
Customer and CustomersWithProductScore tables.
E. From the Power Bl Admin portal, set Make certified content discoverable to
Enabled.
Answer: ADE
QUESTION 3
How should you configure the Power BI dataset refresh for the
dbo.SalesTransactions table?
A. an incremental refresh of Product where the ModifiedDate value is during the
last three days.
B. an incremental refresh of dbo.SalesTransactions where the SalesDate value is
during the last three days.
C. a full refresh of all the tables
D. an incremental refresh of dbo.SalesTransactions where the SalesDate value is
during the last hour.
Answer: B
QUESTION 4
You need to recommend a solution to add new fields to the financial data
Power Bl dataset with data from the Microsoft SQL Server data warehouse.
What should you include in the recommendation?
A. Azure Purview
B. Site-to-Site VPN
C. an XMLA endpoint
D. the on-premises data gateway
Answer: D
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