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Microsoft Power BI Data Analyst Syllabus

Prepare the Data

Covers connecting to data sources, profiling data, cleaning and transforming data using Power Query.

27%
Weight
14
Questions
270
Marks

Connecting to Data Sources

  • Connecting to files: Excel, CSV, JSON, XML, and PDF
  • Connecting to databases: SQL Server, Azure SQL, PostgreSQL, Oracle
  • Connecting to cloud services: SharePoint, Dynamics 365, Salesforce
  • Import mode vs DirectQuery vs Dual mode trade-offs
  • Using parameters and data source credentials

Data Profiling and Quality

  • Column distribution, column quality, and column profile views
  • Identifying nulls, duplicates, and outliers
  • Data types in Power Query and type errors
  • Enabling load vs disabling load for staging queries

Power Query Transformations

  • Filtering, sorting, and removing rows and columns
  • Pivoting and unpivoting columns for normalisation
  • Merging queries: join kinds (inner, left outer, full outer, anti)
  • Appending queries to combine tables
  • Using custom columns, conditional columns, and M expressions
  • Handling errors and replacing values

Advanced Query Techniques

  • Query folding: what it is and how to verify it occurs
  • Grouping and aggregating data in Power Query
  • Extracting data from nested JSON and XML
  • Using reference queries vs duplicate queries

Model the Data

Covers designing and building data models including relationships, DAX calculations, and performance optimisation.

27%
Weight
14
Questions
270
Marks

Data Model Design

  • Star schema vs snowflake schema design principles
  • Fact tables and dimension tables: roles and best practices
  • Creating and managing table relationships in Model view
  • Cardinality: one-to-many, many-to-many, one-to-one
  • Cross-filter direction: single vs both and performance impact
  • Role-playing dimensions and inactive relationships

Calculated Tables and Columns

  • Calculated columns vs measures: when to use each
  • Creating date tables with CALENDAR() and CALENDARAUTO()
  • Marking a date table for time intelligence
  • Calculated tables using FILTER, ALL, and SUMMARIZE

DAX Fundamentals

  • DAX syntax, operators, and data types
  • CALCULATE() function: modifying filter context
  • FILTER(), ALL(), ALLEXCEPT(), and REMOVEFILTERS()
  • Iterator functions: SUMX, AVERAGEX, RANKX
  • Time intelligence functions: TOTALYTD, SAMEPERIODLASTYEAR, DATEADD
  • RELATED() and RELATEDTABLE() for navigating relationships

Advanced DAX Patterns

  • Row context vs filter context and context transition
  • Variables in DAX: VAR and RETURN
  • Measures for percentage of total and running totals
  • Dynamic segmentation with SWITCH() and IF()

Performance Best Practices

  • Reducing model size: removing unused columns and tables
  • Aggregations and pre-aggregation tables
  • Using Performance Analyser to identify slow visuals
  • DAX Studio and Tabular Editor for optimisation
  • Optimising DirectQuery models

Visualise and Analyse the Data

Covers creating reports and dashboards, applying filters, and performing data analysis in Power BI Desktop and Service.

27%
Weight
14
Questions
270
Marks

Visualisation Types and Selection

  • Choosing appropriate visuals: bar, line, scatter, map, pie, treemap
  • Card and multi-row card for KPI display
  • Matrix and table visuals: conditional formatting and totals
  • Waterfall, funnel, and decomposition tree visuals
  • Custom visuals from AppSource

Interactivity and Filtering

  • Slicers: list, dropdown, date range, and relative date
  • Cross-filtering and cross-highlighting between visuals
  • Edit interactions to control visual behaviour
  • Drillthrough pages and report tooltips
  • Buttons, bookmarks, and page navigation

Report Design

  • Themes, templates, and consistent colour palettes
  • Mobile layout and responsive design
  • Accessibility: alt text, tab order, and keyboard navigation
  • Page navigation with buttons and selection pane

Advanced Analytics

  • Analytics pane: trend lines, forecast, and constant lines
  • Q&A visual and natural language queries
  • Key influencers and decomposition tree for explanatory analysis
  • Anomaly detection in line charts
  • Smart narratives for automated text insights

Deploy and Maintain Assets

Covers publishing to Power BI Service, managing workspaces, configuring gateways, and setting up refresh and security.

19%
Weight
9
Questions
190
Marks

Publishing and Workspaces

  • Publishing reports from Desktop to Power BI Service
  • Workspace roles: Admin, Member, Contributor, Viewer
  • Apps: creating, publishing, and updating workspace apps
  • Deployment pipelines: Development, Test, Production stages

Data Refresh and Gateways

  • Scheduled refresh: configuring and troubleshooting
  • On-premises data gateway: standard vs personal mode
  • Incremental refresh policies using RangeStart and RangeEnd
  • Dataflows and their refresh dependencies

Security and Governance

  • Row-level security (RLS): static and dynamic roles
  • Object-level security (OLS) for column and table restrictions
  • Sensitivity labels and Microsoft Purview integration
  • Endorsement: promoting and certifying datasets
  • Lineage view and impact analysis in Power BI Service

Sharing and Collaboration

  • Sharing reports vs sharing dashboards vs publishing apps
  • Embedding reports in SharePoint and Teams
  • Subscriptions and data alerts
  • Usage metrics and monitoring report performance

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Timed Exams

Simulate real exam conditions with timed practice tests

  • Exam-like environment
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Practice Tests

Comprehensive question bank with detailed explanations

  • Latest exam patterns
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Mind Maps

Visual learning tools to connect and remember concepts

  • Interactive diagrams
  • Topic relationships

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Learning Progress

Prepare the Data 85%
Model the Data 92%

Practice Test Scores

95%
Latest Score
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