Implement Security and Governance
- Implement workspace-level access controls
- Implement item-level access controls
- Implement row-level, column-level, object-level, and file-level access control
- Apply sensitivity labels to items
- Endorse items

Maintain the Analytics Development Lifecycle
- Configure version control for a workspace
- Create and manage a Power BI Desktop project (.pbip)
- Create and configure deployment pipelines
- Perform impact analysis of downstream dependencies
- Deploy and manage semantic models using XMLA endpoint
- Create and update reusable assets: .pbit, .pbids, and shared semantic models

Get Data
- Ingest or access data
- Create and manage shortcuts
- Create a data connection
- Discover data using OneLake and Real-time hub
- Choose between lakehouse, warehouse, or eventhouse
- Implement OneLake integration

Transform Data
- Create views, functions, stored procedures
- Enrich data with new columns or tables
- Implement star schema for lakehouse/warehouse
- Denormalize, aggregate, and merge data
- Handle duplicates, nulls, and convert data types
- Filter data

Query and Analyze Data
- Use Visual Query Editor, SQL, and KQL for analysis

Design and Build Semantic Models
- Choose storage mode
- Star schema for semantic models
- Relationships: bridge tables, many-to-many
- DAX: variables, iterators, filtering, windowing, info functions
- Calculation groups and dynamic format strings
- Field parameters and composite models
- Large semantic model storage
- Aggregations
Optimize Enterprise-Scale Semantic Models
- Query and visual performance
- Improve DAX
- Configure Direct Lake behavior
---------------------------------------------
Good luck on your path to becoming a certified Fabric Analytics Engineer!