Business Challenge
Global manufacturing company ($2.5B revenue) struggled with legacy data infrastructure causing 4-hour reporting delays, 25% inventory forecast inaccuracies, and excessive manual processes, leading to approximately $2M annual losses in procurement inefficiencies.
Solution Implemented
- Automated data integration using Azure Data Factory
- Three-tier data lake architecture (Bronze/Silver/Gold)
- Real-time processing capabilities via Azure Databricks
- Enterprise-grade security and governance framework
Architecture Overview
Key Results
- Performance: Reduced report generation from 4 hours to 15 minutes
- Accuracy: Improved data accuracy from 75% to 99.9%
- Efficiency: Achieved 60% reduction in manual effort
- Cost: $1.2M annual savings in operational costs
- Business Impact: 40% improvement in inventory accuracy
Project Timeline
12-week implementation across three phases:
1. Foundation Setup (4 weeks)
- Infrastructure deployment
- Security implementation
- Monitoring setup
2. Data Migration (4 weeks)
- Pipeline development
- Data quality framework
- Performance optimization
3. Business Integration (4 weeks)
- Report migration
- User training
- Production deployment
ROI Highlights
- Payback Period: 14 months
- First Year Cost Savings: $1.2M
- Operational Efficiency Gain: 60%