Use this quick start guide to collect all the information about Microsoft Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI (DP-500) Certification exam. This study guide provides a list of objectives and resources that will help you prepare for items on the DP-500 Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI exam. The Sample Questions will help you identify the type and difficulty level of the questions and the Practice Exams will make you familiar with the format and environment of an exam. You should refer this guide carefully before attempting your actual Microsoft MCA Azure Enterprise Data Analyst certification exam.
The Microsoft Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI certification is mainly targeted to those candidates who want to build their career in Microsoft Azure domain. The Microsoft Certified - Azure Enterprise Data Analyst Associate exam verifies that the candidate possesses the fundamental knowledge and proven skills in the area of Microsoft MCA Azure Enterprise Data Analyst.
Microsoft Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI Exam Summary:
| Exam Name | Microsoft Certified - Azure Enterprise Data Analyst Associate |
| Exam Code | DP-500 |
| Exam Price | $165 (USD) |
| Duration | 120 mins |
| Number of Questions | 40-60 |
| Passing Score | 700 / 1000 |
| Books / Training | DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI |
| Schedule Exam | Pearson VUE |
| Sample Questions | Microsoft Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI Sample Questions |
| Practice Exam | Microsoft DP-500 Certification Practice Exam |
Microsoft DP-500 Exam Syllabus Topics:
| Topic | Details |
|---|---|
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 |
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 - Optimize query performance by using DAX Studio - 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 - Create and distribute paginated reports in Power BI Report Builder |
To ensure success in Microsoft MCA Azure Enterprise Data Analyst certification exam, we recommend authorized training course, practice test and hands-on experience to prepare for Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI (DP-500) exam.