Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI (DP-500) Practice Exam
Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI (DP-500) Practice Exam
Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft
Exam DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI is intended for candidates with specialized knowledge in crafting, deploying, and managing enterprise-level data analytics solutions. Your role entails executing advanced data analytics operations at scale, including:
Data cleansing and transformation.
Development of enterprise data models.
Integration of advanced analytics functionalities.
Incorporation with IT infrastructure.
Adherence to development lifecycle practices.
As a professional in this capacity, your duties include:
Gathering enterprise-level requirements for data analytics solutions incorporating Azure and Power BI.
Providing guidance on data governance and configuration settings for Power BI administration.
Monitoring data utilization.
Enhancing the performance of data analytics solutions.
In your role as an Azure enterprise data analyst, collaboration with various stakeholders is essential, including:
Solution architects
Data engineers
Data scientists
AI engineers
Database administrators
Power BI data analysts
Who should take the exam?
As a candidate preparing for this test, you are expected to possess proficient Power BI abilities, encompassing the management of data repositories and processing both in cloud and on-premises environments. Additionally, you should demonstrate proficiency in utilizing Power Query and Data Analysis Expressions (DAX). Moreover, you should be adept at leveraging data from Azure Synapse Analytics and possess experience in querying relational databases, analyzing data via Transact-SQL (T-SQL), and visualizing data.
Exam Details
Exam Code: DP-500
Exam Name: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI
Exam Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Chinese (Traditional), Italian
Exam Questions: 40-60 Questions
Passing Score: 700 or greater (On a scale 1 - 1000)
Course Outline
The Microsoft DP-500 Exam covers the given topics -
Topic 1: Learn how to 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 type for 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 Azure Synapse Analytics code and artifacts to a source control repository
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 template (.pbit) files, Power BI data source (.pbids) files, and shared datasets
Topic 2: Understand 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
Topic 3: Understand about implementing and managing 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
Optimize query performance by using DAX Studio
Implement incremental refresh (including the use of query folding)
Optimize a data model by using denormalization
Topic 4: Learn about exploring and visualizing 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
Create and distribute paginated reports in Power BI Report Builder