Prepare Data
- Connect data sources or use a shared semantic model; manage credentials and privacy levels
- Choose deliberately between Import, DirectQuery and Direct Lake; create and change parameters
- Profile data: evaluate statistics and column properties, fix inconsistencies, null values and import errors
- Transform: data types, new and changed columns, group and aggregate, pivot and unpivot, turn semi-structured data into tables
- Build fact and dimension tables, merge and append queries, create keys for relationships, control load behaviour
Model Data
- Table and column properties, role-playing dimensions, cardinality and cross-filter direction, shared date table
- DAX: aggregations, CALCULATE, time intelligence, statistical functions, semi-additive measures, calculated tables and columns, calculation groups
- Improve model performance: remove redundant rows and columns, reduce granularity, find weak measures and visuals with Performance Analyzer and the DAX query view
Visualise and Analyse
- Choose the right visuals, format them, apply design and conditional formatting, filter and slice, visual calculations with DAX
- Build reports that tell a story: bookmarks, custom tooltips, interactions between visuals, navigation, drillthrough, sorting, synced slicers
- Design reports for mobile devices and accessibility, personalisation and automatic page refresh
- Spot patterns and trends: Analyze feature, grouping and clustering, AI visuals, reference lines and forecasting, outliers and anomalies
- Copilot in Power BI: have report pages suggested, generate narrative visuals, summarise semantic models
Manage and Secure
- Set up workspaces and apps, publish and refresh content, dashboards, distribution methods, subscriptions and data alerts
- Promote or certify content, identify gateway needs, set up scheduled refresh
- Secure: workspace roles, access to items and semantic models, row-level security including group mapping, sensitivity labels
