Power BI

Exam DA-100: Analyzing Data with Microsoft Power BI

Audience Profile
Data Analysts enable businesses to maximize the value of their data assets by using Power BI. As a subject matter expert, data analysts are responsible for designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value through easy-to-comprehend data visualizations. Data analysts also collaborate with key stakeholders across verticals to deliver relevant insights based on identified business requirements.

The Data Analyst should have a fundamental understanding of data repositories and data processing both on-premises and in the cloud.

Prepare the Data (20-25%)
Get data from different data sources
• Identify and connect to a data source
• Change data source settings
• Select a shared dataset or create a local dataset
• Select a storage mode
• Choose an appropriate query type
• Identify query performance issues
• Use Microsoft Dataverse
• Use parameters
• Use or create a PBIDS file
• Use or create a data flow
• Connect to a dataset using the XMLA endpoint

Profile the data

• Identify data anomalies
• Examine data structures
• Interrogate column properties
• Interrogate data statistics

Clean, transform, and load the data

• Resolve inconsistencies, unexpected or null values, and data quality issues
• Apply user-friendly value replacements
• Identify and create appropriate keys for joins
• Evaluate and transform column data types
• Apply data shape transformations to table structures
• Combine queries
• Apply user-friendly naming conventions to columns and queries
• Leverage advanced editor to modify power query m code
• Configure data loading
• Resolve data import errors

Model the Data (25-30%)
Design a data model
• Define the tables
• Configure table and column properties
• Define quick measures
• Flatten out a parent-child hierarchy
• Define role-playing dimensions
• Define a relationship’s cardinality and cross-filter direction
• Design the data model to meet performance requirements
• Resolve many-to-many relationships
• Create a common date table
• Define the appropriate level of data granularity
• Apply or change sensitivity labels

Develop a data model

• Apply cross-filter direction and security filtering
• Create calculated tables
• Create hierarchies
• Create calculated columns
• Implement row-level security roles
• Implement object-level security
• Set up the q&a feature

Create measures by using DAX

• use DAX to build complex measures
• use CALCULATE to manipulate filters
• implement Time Intelligence using DAX
• replace numeric columns with measures
• use basic statistical functions to enhance data
• create semi-additive measures

Optimize model performance

• remove unnecessary rows and columns
• identify poorly performing measures, relationships, and visuals
• improve cardinality levels by changing data types
• improve cardinality levels through summarization
• create and manage aggregations
• use Query Diagnostics

Visualize the Data (20-25%)
Create reports

• add visualization items to reports
• choose an appropriate visualization type
• format and configure visualizations
• import a custom visual
• configure conditional formatting
• apply slicing and filtering
• add an R or Python visual
• add a Smart Narrative visual
• configure the report page
• design and configure for accessibility
• configure automatic page refresh
• create a paginated report

Create dashboards

• set mobile view
• manage tiles on a dashboard
• configure data alerts
• use the Q&A feature
• add a dashboard theme
• pin a live report page to a dashboard

Enrich reports for usability

• configure bookmarks
• create custom tooltips
• edit and configure interactions between visuals
• configure navigation for a report
• apply sorting
• configure Sync Slicers
• use the selection pane
• use drillthrough and cross filter
• drilldown into data using interactive visuals
• export report data
• design reports for mobile devices

Analyze the Data (10-15%)
Enhance reports to expose insights

• apply conditional formatting
• apply slicers and filters
• perform top N analysis
• explore statistical summary
• use the Q&A visual
• add a Quick Insights result to a report
• create reference lines by using Analytics pane
• use the Play Axis feature of a visualization
• personalize visuals

Perform advanced analysis

• identify outliers
• conduct Time Series analysis
• use anomaly detection
• use groupings and binnings
• use the Key Influencers to explore dimensional variances
• use the decomposition tree visual to break down a measure
• apply AI Insights

Deploy and Maintain Deliverables (10-15%)
Manage datasets
• configure a dataset scheduled refresh
• configure row-level security group membership
• provide access to datasets
• configure incremental refresh settings
• promote or certify Power BI datasets
• identify downstream dataset dependencies
• configure large dataset format

Create and manage workspaces

• create and configure a workspace
• recommend a development lifecycle strategy
• assign workspace roles
• configure and update a workspace app
• publish, import, or update assets in a workspace
• apply sensitivity labels to workspace content
• use deployment pipelines
• configure subscriptions
• promote or certify Power BI content