An event-driven analytics platform built using Microsoft Fabric to streamline campus recruitment by processing placement events, detecting scheduling conflicts, evaluating eligibility, and providing actionable insights through role-based dashboards.
Campus placement information is typically scattered across emails, spreadsheets, and messaging platforms. Students often struggle to:
- Track multiple placement drives simultaneously
- Identify eligibility mismatches
- Detect interview scheduling conflicts
- Prioritize opportunities based on their skillset
- Keep up with changing deadlines and recruitment updates
Placement offices also lack a centralized analytical view of recruitment activities, registrations, interview schedules, and placement progress.
This project demonstrates how a modern data platform can continuously process placement events and transform them into actionable insights.
The Campus Placement Intelligence Platform simulates a real-world placement ecosystem using synthetic data and processes it through a Microsoft Fabric Medallion Architecture.
The platform:
- Processes placement events from multiple sources
- Maintains historical records of recruitment activities
- Detects interview scheduling conflicts
- Evaluates student eligibility against company criteria
- Calculates personalized role-fit scores
- Generates real-time alerts for important events
- Provides separate dashboards for students and placement officers
- Eligible placement drives
- Upcoming deadlines
- Interview schedule
- Interview conflict detection
- Skill-based fit score
- Offer tracking
- Active placement drives
- Registration analytics
- Company participation
- Student eligibility statistics
- Recruitment pipeline
- Hiring trends
- Medallion Architecture
- Incremental data processing
- Delta Lake tables
- Event-driven pipeline
- Data quality validation
- Historical tracking
- Real-time alerts
- Power BI dashboards
Synthetic Event Generator
│
▼
Microsoft Fabric Pipeline
│
┌──────────────────────┐
│ Bronze Layer │
│ Raw placement events │
└──────────────────────┘
│
▼
┌──────────────────────┐
│ Silver Layer │
│ Cleaning & Validation │
└──────────────────────┘
│
▼
┌──────────────────────┐
│ Gold Layer │
│ Analytics & KPIs │
└──────────────────────┘
│
┌─────────────────┴─────────────────┐
▼ ▼
Microsoft Activator Power BI Dashboards
- Raw placement events
- Immutable event log
- Timestamp preservation
- Source tracking
- Data cleansing
- Duplicate removal
- Eligibility normalization
- Skill standardization
- Date validation
- Eligibility engine
- Interview conflict detection
- Role-fit scoring
- Placement KPIs
- Analytical datasets
The platform simulates real-time placement events including:
- Company Added
- Placement Drive Created
- Eligibility Updated
- Student Registered
- Interview Scheduled
- Interview Rescheduled
- Deadline Extended
- Offer Released
- Lakehouse
- OneLake
- Data Pipelines
- Dataflow Gen2
- Notebook
- Activator
- Power BI
- Python
- SQL
- PySpark
- Delta Lake
placement-drive-intelligence
│
├── assets/
├── activator/
├── data/
│ ├── reference_data/
│ └── synthetic_events/
├── docs/
├── event_generator/
├── notebooks/
│ ├── bronze/
│ ├── silver/
│ └── gold/
├── pipelines/
├── powerbi/
├── screenshots/
└── README.md
- Repository initialized
- Microsoft Fabric Workspace created
- Lakehouse created
- Project structure designed
- Synthetic data generation
- Event generator
- Bronze pipeline
- Silver transformations
- Gold analytics
- Activator alerts
- Power BI dashboard
- Documentation
Clone the repository:
git clone https://github.com/flimsycelery/placement-drive-intelligence.git
cd placement-drive-intelligenceCreate a virtual environment:
python -m venv .venvActivate it:
Windows
.venv\Scripts\activateInstall dependencies:
pip install -r requirements.txt- Streaming ingestion
- Predictive placement analytics
- Resume-to-role matching
- AI-powered company recommendations
- Fabric Real-Time Intelligence integration
- Semantic model optimization
Tanvi Pushparaj
Bachelor of Engineering (Computer Science - Data Science)
Microsoft Fabric | Azure | Data Engineering | Analytics