Production-ready, enterprise-scale modern data platform built on Microsoft Fabric and Azure services, designed for real-time fraud detection, IoT predictive maintenance, and customer analytics. This platform leverages infrastructure as code for complete automation and reproducibility.
- Sub-second transaction scoring
- ML-powered anomaly detection
- Real-time alerting and case management
- Historical pattern analysis
- High-volume sensor data ingestion
- Real-time equipment health monitoring
- Predictive failure analysis
- Maintenance scheduling optimization
- Customer segmentation
- Sales forecasting
- Marketing campaign effectiveness
- Customer lifetime value prediction
┌──────────────────────────────────────────────────────────────────────────────┐
│ DATA SOURCES │
├───────────────────┬──────────────────┬──────────────────┬────────────────────┤
│ 🏦 Transaction │ 🏭 IoT Sensors │ 📊 Sales/CRM │ 🌐 External APIs │
│ • Banking Core │ • Temperature │ • Salesforce │ • Weather Data │
│ • Payment Gateways│ • Vibration │ • Dynamics 365 │ • Market Data │
│ • POS Systems │ • Pressure │ • Marketing Hub │ • Social Media │
└────────┬──────────┴───────┬──────────┴───────┬──────────┴──────────┬──────────┘
│ │ │ │
▼ ▼ ▼ ▼
┌───────────────────────────────────────────────────────────────────────────────┐
│ INGESTION LAYER (Azure) │
├───────────────────────────────────────────────────────────────────────────────┤
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ ┌───────────────┐ │
│ │ 📡 Event Hub │ │ 🔌 IoT Hub │ │ 🔄 Data Factory │ │ 📥 Storage │ │
│ │ • Streaming │ │ • Device Mgmt │ │ • Batch ETL │ │ • Blob/ADLS │ │
│ │ • Partitioned │ │ • Twin Support │ │ • Scheduled │ │ • Landing Zone│ │
│ │ • Auto-scale │ │ • Edge Process │ │ • Triggered │ │ │ │
│ └────────┬────────┘ └────────┬────────┘ └────────┬────────┘ └───────┬───────┘ │
└──────────┼───────────────────┼───────────────────┼──────────────────┼─────────┘
│ │ │ │
▼ ▼ ▼ ▼
┌──────────────────────────────────────────────────────────────────────────────┐
│ MICROSOFT FABRIC WORKSPACE │
├──────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌────────────────────────────────────────────────────────────────────────┐ │
│ │ 🗄️ ONELAKE (Unified Storage) │ │
│ ├────────────────────────────────────────────────────────────────────────┤ │
│ │ ┌──────────────────┐ ┌──────────────────┐ ┌──────────────────┐ │ │
│ │ │ 🥉 BRONZE Layer │ │ 🥈 SILVER Layer │ │ 🥇 GOLD Layer │ │ │
│ │ │ • Raw Data │ │ • Cleansed Data │ │ • Business Ready │ │ │
│ │ │ • Immutable │──▶│ • Validated │──▶│ • Aggregated │ │ │
│ │ │ • Partitioned │ │ • Deduplicated │ │ • Optimized │ │ │
│ │ │ • Delta Format │ │ • Standardized │ │ • Star Schema │ │ │
│ │ └──────────────────┘ └──────────────────┘ └──────────────────┘ │ │
│ └────────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌────────────────────────────────────────────────────────────────────────┐ │
│ │ 🔧 PROCESSING & ANALYTICS │ │
│ ├────────────────────────────────────────────────────────────────────────┤ │
│ │ │ │
│ │ ┌─────────────────────────┐ ┌─────────────────────────────────┐ │ │
│ │ │ ⚡ Real-Time Analytics │ │ 🏗️ Data Engineering │ │ │
│ │ │ • KQL Database │ │ • Spark Processing │ │ │
│ │ │ • Stream Processing │ │ • Data Pipelines │ │ │
│ │ │ • Hot Path Analytics │ │ • Transformation Jobs │ │ │
│ │ └─────────────────────────┘ └─────────────────────────────────┘ │ │
│ │ │ │
│ │ ┌─────────────────────────┐ ┌─────────────────────────────────┐ │ │
│ │ │ 🏢 Data Warehouse │ │ 🤖 Data Science & ML │ │ │
│ │ │ • Synapse SQL │ │ • ML Notebooks │ │ │
│ │ │ • Dimensional Models │ │ • Model Training │ │ │
│ │ │ • Business Logic │ │ • Feature Engineering │ │ │
│ │ └─────────────────────────┘ └─────────────────────────────────┘ │ │
│ └────────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌────────────────────────────────────────────────────────────────────────┐ │
│ │ 📊 SEMANTIC LAYER │ │
│ ├────────────────────────────────────────────────────────────────────────┤ │
│ │ • Business Metrics • Data Models • Calculated Measures │ │
│ │ • KPIs & Scorecards • Relationships • Row-Level Security │ │
│ └────────────────────────────────────────────────────────────────────────┘ │
└──────────────────────────────────────────────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────────────────┐
│ CONSUMPTION & SERVING LAYER │
├──────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────────┐ ┌──────────────────┐ ┌──────────────────────────┐ │
│ │ 📈 Power BI │ │ 🔌 API Gateway │ │ 🎯 Applications │ │
│ │ • Dashboards │ │ • REST APIs │ │ • Fraud Alert System │ │
│ │ • Reports │ │ • GraphQL │ │ • Maintenance Portal │ │
│ │ • Real-time │ │ • Rate Limiting │ │ • Customer 360 View │ │
│ └──────────────────┘ └──────────────────┘ └──────────────────────────┘ │
│ │
│ ┌──────────────────┐ ┌──────────────────┐ ┌──────────────────────────┐ │
│ │ 🤖 ML Endpoints │ │ 📱 Mobile Apps │ │ 🔔 Alerting & Actions │ │
│ │ • Model Serving │ │ • iOS/Android │ │ • Email/SMS/Teams │ │
│ │ • A/B Testing │ │ • Offline Sync │ │ • Automated Workflows │ │
│ │ • AutoML APIs │ │ • Push Notif. │ │ • Incident Management │ │
│ └──────────────────┘ └──────────────────┘ └──────────────────────────┘ │
└──────────────────────────────────────────────────────────────────────────────┘
┌─────────────────────────┐
│ 🔐 SECURITY LAYER │
├─────────────────────────┤
│ • Azure AD / Entra ID │
│ • RBAC & Permissions │
│ • Data Encryption │
│ • Network Security │
│ • Compliance (GDPR/PCI) │
└─────────────────────────┘
Credit Card Transaction → Event Hub → KQL Database (Hot Path)
↓
Real-time Scoring (< 1 sec)
↓
Alert Generation → Case Management
↓
Historical Analysis → ML Model Update
Sensor Data → IoT Hub → Stream Analytics → Time Series Database
↓
Anomaly Detection Model
↓
Maintenance Prediction → Work Order System
↓
Historical Pattern Analysis → Model Retraining
CRM/Sales Data → Data Factory → Bronze Layer → Silver Layer
↓
Customer Segmentation
↓
Gold Layer (Aggregated)
↓
Power BI Dashboards → Business Insights
azure-fabric-data-platform/
├── infrastructure/ # Infrastructure as Code
│ ├── terraform/ # Terraform configurations
│ │ ├── environments/ # Environment-specific configs
│ │ ├── modules/ # Reusable Terraform modules
│ │ └── scripts/ # Deployment scripts
│ ├── bicep/ # Bicep templates (alternative)
│ └── arm/ # ARM templates (legacy support)
├── pipelines/ # Data pipeline definitions
│ ├── ingestion/ # Data ingestion pipelines
│ ├── transformation/ # Data transformation logic
│ └── orchestration/ # Orchestration workflows
├── ml-models/ # Machine Learning models
│ ├── fraud-detection/ # Fraud detection models
│ ├── predictive-maintenance/ # Maintenance models
│ └── customer-analytics/ # Customer models
├── notebooks/ # Data science notebooks
├── apis/ # API definitions and code
├── monitoring/ # Monitoring and alerting configs
├── governance/ # Data governance policies
├── tests/ # Testing frameworks
├── docs/ # Documentation
└── .github/ # CI/CD workflows
- Microsoft Fabric: Unified analytics platform
- Azure Data Lake Storage Gen2: OneLake storage backend
- Azure Synapse Analytics: Data warehousing and big data analytics
- Azure Databricks: Advanced analytics and ML (optional alternative)
- Azure Event Hubs: High-throughput event streaming
- Azure IoT Hub: IoT device connectivity and management
- Azure Stream Analytics: Real-time stream processing
- Fabric Real-Time Analytics: KQL-based real-time analytics
- Azure Machine Learning: ML model development and deployment
- Fabric Data Science: Integrated ML workflows
- Azure Cognitive Services: Pre-built AI models
- Azure Data Factory: Data movement and orchestration
- Azure Logic Apps: Workflow automation
- Azure Functions: Serverless compute
- Azure Monitor: Infrastructure and application monitoring
- Microsoft Purview: Data governance and compliance
- Azure Key Vault: Secrets management
- Azure Security Center: Security posture management
- Azure subscription with appropriate permissions
- Microsoft Fabric capacity (F64 or higher recommended for production)
- Azure DevOps or GitHub account for CI/CD
- Terraform >= 1.5.0 or Bicep CLI
- Azure CLI >= 2.50.0
- PowerShell 7+ or Bash
- Clone the repository
git clone https://github.com/yourusername/azure-fabric-data-platform.git
cd azure-fabric-data-platform- Configure environment
cd infrastructure/terraform/environments
cp dev.tfvars.example dev.tfvars
# Edit dev.tfvars with your settings- Deploy infrastructure
cd ../
terraform init
terraform plan -var-file=environments/dev.tfvars
terraform apply -var-file=environments/dev.tfvars- Deploy pipelines
cd ../../pipelines
./deploy-pipelines.sh dev- Deploy ML models
cd ../ml-models
./deploy-models.sh devTransaction → Event Hub → Stream Analytics → ML Scoring → Alert/Block
↓
OneLake → Batch Training → Model Update
Sensors → IoT Hub → Time Series Insights → Anomaly Detection
↓
OneLake → Feature Engineering → Predictive Model → Maintenance Schedule
CRM/Sales → Data Factory → OneLake → Transformation → Data Warehouse
↓
ML Pipeline → Segmentation/Forecasting
- Network Security: Private endpoints, VNet integration
- Data Security: Encryption at rest and in transit
- Access Control: Azure AD integration, RBAC
- Compliance: PCI DSS, GDPR, HIPAA ready
- Data Governance: Purview integration for lineage and cataloging
- Auto-scaling: Dynamic resource allocation
- Partitioning: Optimized data partitioning strategies
- Caching: Intelligent caching layers
- CDN Integration: Global content delivery for APIs
- Reserved Capacity: Fabric capacity reservations
- Lifecycle Management: Automated data archival
- Resource Tagging: Cost allocation and tracking
- Auto-pause: Development environment auto-shutdown
- Infrastructure: Terraform/Bicep deployment pipelines
- Data Pipelines: Automated pipeline deployment
- ML Models: MLOps pipeline for model deployment
- Testing: Automated testing at all layers
Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.
This project is licensed under the MIT License - see the LICENSE file for details.
- Create an issue in GitHub
- Check the FAQ
- Review the Troubleshooting Guide
- Microsoft Fabric Product Team
- Azure Architecture Center
- Community contributors
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