Development Notice: Backend integration in progress. Currently using static demo data for demonstration purposes.
Python-based ETL pipeline for ERP systems featuring automated data extraction, validation, schema mapping, and real-time KPI analytics with Power BI integration
Connect to ERP database and execute SQL queries for fact tables
Normalize columns, validate datasets, and handle missing values
Generate sales margins, labor efficiency, and inventory metrics
Create CSV exports optimized for business intelligence dashboards
| File | Status | Records | Last Updated | KPI Impact |
|---|---|---|---|---|
| fact_sales_margin.csv | PROCESSED | 1,234 | 2 min ago | Revenue: +$45.2K |
| fact_labor_efficiency.csv | PROCESSED | 856 | 5 min ago | Efficiency: 87.2% |
| fact_inventory_on_hand.csv | LOW STOCK | 156 | 1 min ago | 12 SKUs below threshold |
| supplier_lead_time.csv | PROCESSED | 45 | 8 min ago | Avg: 14 days |
Machine learning algorithms establish normal behavior patterns for users, systems, and network traffic to detect deviations in real-time.
Intelligent event correlation across multiple security tools and data sources to reduce false positives and identify attack chains.
Advanced statistical models predict potential security incidents before they occur, enabling proactive threat mitigation.
Stream processing architecture handles millions of security events per day with sub-second detection and alerting capabilities.
Turn security logs into actionable intelligence with behavioral analytics
View Documentation Source Code