Power-Bi-Performance-Troubleshooting

Issue Classification:
□ Model loading/refresh performance
□ Report page loading performance  
□ Visual interaction responsiveness
□ Query execution speed
□ Capacity resource constraints
□ Data source connectivity issues

Scope Assessment:
□ Affects all users vs. specific users
□ Occurs at specific times vs. consistently
□ Impacts specific reports vs. all reports
□ Happens with certain data filters vs. all scenarios

Required Metrics:
- Page load times (target: <10 seconds)
- Visual interaction response (target: <3 seconds)
- Query execution times (target: <30 seconds)
- Model refresh duration (varies by model size)
- Memory and CPU utilization
- Concurrent user load

Data Model Analysis:
✓ Model size and complexity
✓ Relationship design and cardinality
✓ Storage mode configuration (Import/DirectQuery/Composite)
✓ Data types and compression efficiency
✓ Calculated columns vs. measures usage
✓ Date table implementation

Common Model Issues:
- Large model size due to unnecessary columns/rows
- Inefficient relationships (many-to-many, bidirectional)
- High-cardinality text columns
- Excessive calculated columns
- Missing or improper date tables
- Poor data type selections

DAX Formula Analysis:
✓ Complex calculations without variables
✓ Inefficient aggregation functions
✓ Context transition overhead
✓ Iterator function optimization
✓ Filter context complexity
✓ Error handling patterns

Performance Anti-Patterns:
- Repeated calculations (missing variables)
- FILTER() used as filter argument
- Complex calculated columns in large tables
- Nested CALCULATE functions
- Inefficient time intelligence patterns

Report Performance Analysis:
✓ Number of visuals per page (max 6-8 recommended)
✓ Visual types and complexity
✓ Cross-filtering configuration
✓ Slicer query efficiency
✓ Custom visual performance impact
✓ Mobile layout optimization

Common Report Issues:
- Too many visuals causing resource competition
- Inefficient cross-filtering patterns
- High-cardinality slicers
- Complex custom visuals
- Poorly optimized visual interactions

Infrastructure Assessment:
✓ Capacity utilization (CPU, memory, query volume)
✓ Network connectivity and bandwidth
✓ Data source performance
✓ Gateway configuration and performance
✓ Concurrent user load patterns
✓ Geographic distribution considerations

Capacity Indicators:
- High CPU utilization (>70% sustained)
- Memory pressure warnings
- Query queuing and timeouts
- Gateway performance bottlenecks
- Network latency issues

Performance Analyzer:
- Enable and record visual refresh times
- Identify slowest visuals and operations
- Compare DAX query vs. visual rendering time
- Export results for detailed analysis

Usage:
1. Open Performance Analyzer pane
2. Start recording
3. Refresh visuals or interact with report
4. Analyze results by duration
5. Focus on highest duration items first

Advanced DAX Analysis:
- Query execution plans
- Storage engine vs. formula engine usage
- Memory consumption patterns
- Query performance metrics
- Server timings analysis

Key Metrics to Monitor:
- Total duration
- Formula engine duration
- Storage engine duration
- Scan count and