Case Study #1 :- Azure IoT Predictive Maintenance
Industry: Manufacturing (Smart Factory)
🔹 Business Issue
- Machines failing without warning
- Expensive spare parts kept in stock “just in case”
☁️ Cloud Solution — Azure
- IoT Hub + Stream Analytics for sensor data
- Time-series ML via Azure Machine Learning
- Automated technician dispatch via logic apps
📈 Outcomes
KPI | Result |
Unplanned downtime | –35% |
Spare inventory cost | –21% |
Safety incidents | –12% |
Predict → Prevent → Profit
Case Study #2 — Multi-Cloud Cost Explosion Control
Industry: IT Services / SaaS Provider
❌ Customer Problems
- Costs unpredictable due to idle resources + over-provisioning
- Finance team struggled to forecast cloud budget
- Dev teams spun up infra without governance
☁️ Cloud Solution
- FinOps practice + AWS + Azure Cost Optimization
- Automated rightsizing policies
- Reserved Instances + Spot usage
- Tag-based chargeback to teams
📈 Results
KPI | Impact |
Monthly cloud bill | –38% |
Idle compute | –72% |
Cost forecast accuracy | +32% |
📌 Case Study #3 — Zero-Downtime SAP Migration to Azure
Industry: Large Manufacturing Enterprise
Systems: SAP ECC → S/4HANA on Azure
❌ Problems
- SAP hosted on aging servers → outages during quarter-end runs
- Hardware refresh would cost millions
- Scaling issues during MRP execution
☁️ Solution
- Azure Migrate + HANA Large Instances
- Availability Zones + DR in secondary region
- Automated Scale-Out for month-end load
📈 Impact
Metric | Before | After |
Downtime | 10 hrs/month | 0 hrs/month |
MRP batch processing | 9 hrs | 2.5 hrs |
Hardware OpEx | –45% |
📌 Case Study #4 — AWS Data Mesh for Global Retail
Industry: E-commerce / Retail (12 Countries)
❌ Problems
- Central data warehouse couldn’t scale
- Regional teams blocked waiting for global IT
- Reporting latency 2–3 days
☁️ Solution
- Data Mesh on AWS Lake Formation
- Domain-owned data products (each country → own pipeline)
- Governance + discovery via Glue Catalog
📈 Results
KPI | Result |
Reporting speed | 2 days → < 5 mins |
Data Engineering backlog | –60% |
Region self-service access | 100% adoption |