DP-600

Implementing Analytics Solutions Using Microsoft Fabric

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Topics

Maintain a data analytics solution25-30%

Implement security and governance

✓Workspace role scope: workspace vs capacity vs tenant6q✓Item permissions vs workspace roles5q✓Row-level security implementation in Fabric Warehouse</>5q✓Sensitivity label downstream inheritance direction5q✓Endorse items5q

Maintain the analytics development lifecycle

✓Configure version control for a workspace5q✓Create and manage a Power BI Desktop project (.pbip)5q✓Deployment pipeline workspace requirements5q✓Impact analysis vs lineage view for cross-workspace downstream items5q✓Deploy and manage semantic models by using the XMLA endpoint</>5q✓Power BI template file characteristics5q

Prepare data45-50%

Get data

✓Create a data connection</>7q✓OneLake catalog vs Real-Time hub7q✓Ingest or access data as needed</>7q✓Choose between different data stores8q✓Eventhouse OneLake Availability - what it does7q

Transform data

✓Create views, functions, and stored procedures</>8q✓Enrich data by adding new columns or tables</>8q✓Star schema: surrogate keys in a Fabric Warehouse dimension table</>7q✓Denormalize data</>7q✓Aggregate data</>8q✓T-SQL MERGE with WHEN NOT MATCHED BY SOURCE in Fabric Warehouse</>8q✓T-SQL NULL comparison operator</>7q✓Convert column data types</>7q✓Filter data</>8q

Query and analyze data

✓Visual Query Editor limitations and DML support6q✓Lakehouse SQL analytics endpoint DML restriction</>10q✓KQL project vs extend column selection</>11q✓CALCULATE filter context overwrite</>10q

Implement and manage semantic models25-30%

Design and build tabular models

✓Choose a storage mode5q✓Implement a star schema for a semantic model5q✓Implement relationships, such as bridge tables and many-to-many relationships</>5q✓DAX VAR filter context capture</>10q✓Calculation groups - SELECTEDMEASURE() vs SELECTEDVALUE()</>7q✓Large semantic model storage format5q✓Design and build composite models5q

Optimize enterprise-scale tabular models

✓Identifying DAX vs visual display bottleneck with Performance Analyzer5q✓Improve DAX performance</>8q✓Configure Direct Lake - Framing vs Import Refresh6q✓Choose between Direct Lake on OneLake and Direct Lake on SQL endpoints5q✓Implement incremental refresh for semantic models5q

301 questions available