Exam DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI – Beta is waiting for you with discount code!

Exam DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI, is the exam that will give you access to the new Microsoft Certified: Azure Enterprise Data Analyst Associate .

The exam DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI is made for candidate expert in 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.

From today it is finally possible to take this exam in Beta and it is possible to get 80 percent off market price by using the code DP500CARLSBAD. The code is not private and the seats are offered on a first-come, first-served basis.

You can take the exam in beta with the code below before May 17, 2022!

Skills measured

• 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 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

If you never took a Microsoft Certification, have a look at Value of a Certification!

Good luck!