New Certification: Microsoft Certified Azure Enterprise Data Analyst Associate

New Certification: Microsoft Certified Azure Enterprise Data Analyst Associate

April 9, 2022 8 By Andy

Microsoft has created a new certification, the Microsoft Certified Azure Enterprise Data Analyst Associate (link here). There is a single exam with a pass rate of 70%: Exam DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI (beta) (link here). The exam is due to be released into beta min-April.

“Candidates for the Azure Enterprise Data Analyst Associate certification should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions.” Microsoft

It’s an interesting certification as it spans multiple Azure data services including Power BI, Synapse Analytics, Purview, DevOps, Data Lake Gen2, and external Power BI tools.

The certification overview is here. Below is a breakdown of the exam requirements and links to learning resources. There is a role relationship diagram to show who works with the Azure Enterprise Data Analyst. I’ve also created a basic architecture diagram to show how the services are linked together after reading through the skills measured.

Who is this certification aimed at? What role does the person who takes this certification play in an organisation? What does an Azure Enterprise Data Analyst do, according to Microsoft? Let’s break the certification down.

There is a video on YouTube in which I give my thoughts on the new certification here.


Responsibilities include…

  • Performing advanced data analytics at scale
  • Cleaning and transforming data
  • Designing and building enterprise data models
  • Incorporating advanced analytics capabilities
  • Integrating with IT infrastructure
  • 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
  • Optimize performance of the data analytics solutions

Candidates should have…

  • Advanced Power BI skills
  • Managing data repositories & data processing in the cloud and on-premises
  • Power Query and Data Analysis Expressions (DAX).
  • Proficient in consuming data from Azure Synapse Analytics
  • Experience querying relational databases
  • Analyzing data by using Transact-SQL (T-SQL)
  • Visualizing data

Collaboration

Who does the Azure Enterprise Data Analyst work/collaborate with? Below is a list of the roles that Microsoft has identified as being relevant to this role.


Data Platform Services

From looking at the skills measured, we can build up a picture of how the services work together.


Skills Measured

There are 4 main categories of skills being measured with 49 discrete skills. Below is a list of skills within each category. There are links to Microsoft documentation and Learn material relevant to each skill.

  • 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%)

Microsoft have put together some relevant Learn collections which you can find links to below. Please reach out on Twitter with any amendments you feel represent the skills measured.

Collections – 23110622 | Microsoft Docs

Collections – 23110622 | Microsoft Docs

Collections – 23110622 | Microsoft Docs

I have started to add links to relevant learning resources for each of the skills measured.

Implement and manage a data analytics environment (25–30%)

Govern and administer a data analytics environment

SkillLearning
Manage Power BI assets by using Azure PurviewDocs | Wolfgang Strasser
Identify data sources in Azure by using Azure PurviewDocs | Learn
Recommend settings in the Power BI admin portalDocs | Learn | Learn
Recommend a monitoring and auditing solution for a data analytics environment, including Power BI REST API and PowerShell cmdletsDocs | Docs

Integrate an analytics platform into an existing IT infrastructure

SkillLearning
Identify requirements for a solution, including features, performance, and licensing strategyDocs | Docs
Configure and manage Power BI capacityDocs | Learn
Recommend and configure an on-premises gateway in Power BIDocs | Docs | Learn
Recommend and configure a Power BI tenant or workspace to integrate with Azure Data Lake Storage Gen2Docs
Integrate an existing Power BI workspace into Azure Synapse AnalyticsDocs | Learn

Manage the analytics development lifecycle

SkillLearning
Commit code and artefacts to a source control repository in Azure Synapse AnalyticsDocs
Recommend a deployment strategy for Power BI assetsDocs | Docs
Recommend a source control strategy for Power BI assetsHavens Consulting with Steve Campbell
Implement and manage deployment pipelines in Power BIDocs
Perform impact analysis of downstream dependencies from dataflows and datasetsDocs
Recommend automation solutions for the analytics development lifecycle, including Power BI REST API and PowerShell cmdletsDocs
Deploy and manage datasets by using the XMLA endpointDocs
Create reusable assets, including Power BI templates, Power BI data source (.pbids) files, and shared datasetsTemplates, PBIDS, Shared Dataset

Query and transform data (20–25%)

Query data by using Azure Synapse Analytics

SkillLearning
Identify an appropriate Azure Synapse pool when analyzing dataDocs | Docs
Recommend appropriate file types for querying serverless SQL poolsDocs | Learn
Query relational data sources in dedicated or serverless SQL pools, including querying partitioned data sourcesDocs | Docs
Use a machine learning PREDICT function in a queryDocs | Docs

Ingest and transform data by using Power BI

SkillLearning
Identify data loading performance bottlenecks in Power Query or data sourcesDocs
Implement performance improvements in Power Query and data sourcesDocs
Create and manage scalable Power BI dataflowsDocs
Identify and manage privacy settings on data sourcesDocs, Docs
Create queries, functions, and parameters by using the Power Query Advanced EditorDocs, Functions, Parameters
Query advanced data sources, including JSON, Parquet, APIs, and Azure Machine Learning modelsJSON, Machine Learning

Implement and manage data models (25–30%)

Design and build tabular models

SkillLearning
Choose when to use DirectQuery for Power BI datasetsDocs
Choose when to use external tools, including DAX Studio and Tabular Editor 2Docs
Create calculation groupsDocs, SQLBI
Write calculations that use DAX variables and functions, for example handling blanks or errors, creating virtual relationships, and working with iteratorsVariables, Functions, IFERROR, USERELATIONSHIP
Design and build a large format datasetDocs
Design and build composite models, including aggregationsComposite Models, Aggregations
Design and implement enterprise-scale row-level security and object-level securityRLS, OLS

Optimize enterprise-scale data models

SkillLearning
Identify and implement performance improvements in queries and report visuals
Troubleshoot DAX performance by using DAX StudioSQLBI, SQLBI
Optimize a data model by using Tabular Editor 2Tabular Editor
Analyze data model efficiency by using VertiPaq AnalyzerFourMoo, SQLBI
Implement incremental refreshDocs
Optimize a data model by using denormalizationDocs

Explore and visualize data (20–25%)

Explore data by using Azure Synapse Analytics

SkillLearning
Explore data by using native visuals in Spark notebooksDocs, Docs
Explore and visualize data by using the Azure Synapse SQL results paneMS YouTube

Visualize data by using Power BI

SkillLearning
Create and import a custom report themeDocs
Create R or Python visuals in Power BIPython, R
Connect to and query datasets by using the XMLA endpointDocs
Design and configure Power BI reports for accessibilityDocs
Enable personalized visuals in a reportDocs
Configure automatic page refreshDocs
Create and distribute paginated reports in Power BI Report BuilderDocs
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