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 Microsoft 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.

Skills Measured

NOTE: The bullets that appear below each of the skills measured are intended to illustrate how we are assessing that skill.
This list is not definitive or exhaustive.
NOTE: In most cases, exams do NOT cover preview features, and some features will
only be added to an exam when they are GA (General Availability).

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 the Common Data Service (CDS)
  • use parameters

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 granularityDevelop a data model
  • apply cross-filter direction and security filtering
  • create calculated tables
  • create hierarchies
  • create calculated columns
  • implement row-level security roles
  • 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
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 conditionalformatting
  • apply slicing and filtering
  • add an R or Python visual
  • configure the report page
  • design and configure for accessibility
  • configure automatic page refresh

Create dashboards

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

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

Perform advanced analysis

  • identify outliers
  • conduct Time Series analysis
  • 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
  • providing access to datasets
  • configure incremental refresh settings
  • endorse a dataset
  • promote or certify a dataset

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
Course(s):
DA-100: Analyzing Data with Power BI – Official Microsoft Course
Certification(s):
Microsoft Certified: Data Analyst Associate