Power BI Reports & Semantic Model¶

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Last Updated: 2025-01-21 | Version: 1.0.0

Overview¶

This directory contains the complete Power BI reporting infrastructure for the Microsoft Fabric Casino/Gaming POC. It includes:

• Semantic Model Definitions (TMDL format) for Direct Lake connectivity
• DAX Measure Libraries organized by business domain
• Report Layout Definitions in JSON format
• Setup and Configuration Guides

Directory Structure¶

reports/
├── README.md                          # This file
├── setup-guide.md                     # Step-by-step setup instructions
├── dax-measures.md                    # Complete DAX reference
├── semantic-model/
│   ├── model.tmdl                     # Model metadata and configuration
│   └── tables/
│       ├── dim_date.tmdl             # Date dimension
│       ├── dim_time.tmdl             # Time dimension
│       ├── dim_machine.tmdl          # Slot machine dimension
│       ├── dim_player.tmdl           # Player dimension
│       ├── dim_table.tmdl            # Table games dimension
│       ├── fact_slot_performance.tmdl # Slot performance facts
│       ├── fact_table_performance.tmdl # Table games facts
│       ├── fact_player_activity.tmdl  # Player 360 facts
│       └── fact_compliance.tmdl       # Compliance facts
│   └── measures/
│       ├── _casino_kpis.tmdl         # Core casino metrics
│       ├── _player_analytics.tmdl    # Player metrics
│       ├── _compliance_metrics.tmdl  # Compliance metrics
│       └── _time_intelligence.tmdl   # Time calculations
└── report-definitions/
    ├── casino-executive-dashboard.json  # Executive summary report
    ├── slot-floor-operations.json       # Slot operations report
    └── compliance-monitoring.json       # Compliance report

Reports Overview¶

1. Casino Executive Dashboard¶

Purpose: High-level KPIs and trends for casino executives

Screenshot Placeholder:

📸 Screenshot: Executive Dashboard showing KPI cards, revenue trends, and player distribution

To add: Capture the main dashboard view from Power BI Service after publishing

Key Filters: - Date Range (default: Last 30 days) - Property/Location - Zone - Denomination

2. Slot Floor Operations¶

Purpose: Operational insights for floor managers

Screenshot Placeholder:

📸 Screenshot: Slot Operations dashboard with floor map and performance metrics

To add: Capture the slot operations view showing machine status and KPIs

Key Filters: - Date Range - Zone - Denomination - Manufacturer - Machine Type - Performance Status

3. Compliance Monitoring¶

Purpose: Regulatory compliance tracking and audit support

Screenshot Placeholder:

📸 Screenshot: Compliance Monitoring dashboard with filing status and deadline tracking

To add: Capture the compliance view showing CTR/SAR/W-2G metrics

Key Filters: - Date Range - Filing Type (CTR, SAR, W-2G) - Filing Status - Amount Threshold

Data Source Configuration¶

Direct Lake Connection¶

The semantic model uses Direct Lake mode for optimal performance:

OneLake (lh_gold lakehouse)
    └── Delta Tables
         ├── gold_slot_performance
         ├── gold_table_analytics
         ├── gold_player_360
         ├── gold_financial_summary
         ├── gold_compliance_reporting
         └── gold_security_dashboard

Connection String Format¶

Data Source=powerbi://api.powerbi.com/v1.0/myorg/[workspace-name];
Initial Catalog=[lakehouse-name];
DirectLakeConnection=True

Required Permissions¶

Key Metrics Reference¶

Slot Performance Metrics¶

Player Metrics¶

Compliance Metrics¶

How to Import into Fabric¶

Method 1: Via Lakehouse UI¶

1. Open lh_gold lakehouse in Fabric
2. Click New semantic model
3. Select all Gold layer tables
4. Configure relationships per setup-guide.md
5. Add measures from dax-measures.md

Method 2: Via TMDL Import¶

1. Export semantic model as TMDL from an existing model
2. Replace table/measure definitions with files from this directory
3. Import modified TMDL to Fabric workspace

Method 3: Via Power BI Desktop¶

1. Connect to OneLake with Direct Lake mode
2. Import tables from lh_gold
3. Create relationships and measures
4. Publish to Fabric workspace

See setup-guide.md for detailed step-by-step instructions.

Report Distribution¶

Scheduled Delivery¶

Row-Level Security¶

RLS is configured for zone-based access:

// Users see only their assigned zones
[Zone Filter] =
    gold_slot_performance[zone] IN VALUES(SecurityTable[UserZone])

Performance Optimization¶

Pre-Aggregation¶

Gold layer tables are pre-aggregated for optimal Direct Lake performance: - Daily grain for historical analysis - Hourly grain for operational dashboards - Optimized with Z-ORDER on frequently filtered columns

Best Practices¶

1. Limit columns - Only include needed fields in semantic model
2. Use measures - Avoid calculated columns for complex logic
3. Filter early - Apply filters at data source level
4. Limit visuals - Maximum 6-8 visuals per report page

Maintenance¶

Monthly Tasks¶

• Review measure performance
• Validate data quality scores
• Update threshold parameters
• Archive old report versions

Quarterly Tasks¶

• Review with business stakeholders
• Add new measures as needed
• Update documentation
• Performance benchmark

Troubleshooting¶

Common Issues¶

Support¶

• Technical: Review troubleshooting section in setup guide
• Business: Contact casino analytics team
• Fabric: Microsoft Fabric documentation

Related Documentation¶

Documentation maintained by: Frank Garofalo Repository: Suppercharge_Microsoft_Fabric