Key results
80% reduction
in reporting time – brought down latency from 3 hours to just 35 minutes
5+ data sources
unified into a centralized Snowflake-powered warehouse
7+ plants
now have real-time visibility into operations and supply chain performance
One Scalable Cloud Foundation
built for future IoT integration and AI-driven use cases
About the Client
A U.S.-based HVAC and building automation systems manufacturer operating multiple plants and distribution hubs. Their on-premise SQL Server environment and fragmented systems led to delays and limited supply chain visibility.
Key Challenges
Legacy SQL Server environment lacked scalability and was costly to maintain
Siloed ERP, MES, and logistics data delayed operational decisions
Daily plant and supply chain reports took over 3 hours to generate
Our Approach
Assessment & Planning
- Assessed legacy SQL Server setup and key production data sources
- Defined a modern data architecture leveraging Snowflake on AWS
- Prioritized high-value datasets for migration
Data Integration & Migration
- Migrated 5+ years of data from SQL Server to Snowflake
- Built Python-based ETL pipelines for ERP, MES, and logistics systems
- Introduced validation rules and audit logging for trustable data
Cloud Warehouse Design
- Organized data into zones: Production, SCM, Inventory
- Developed reusable data marts for performance and operations teams
- Ensured compatibility with existing in-house BI tools
Reporting Acceleration
- Automated daily updates for throughput, order status, and inventory
- Reduced report generation time through Snowflake’s compute model
- Delivered real-time dashboards across 7 manufacturing sites
Implemented Solution
Cloud Data Platform Setup
- Deployed Snowflake on AWS as the centralized data warehouse
- Consolidated data from SQL Server, ERP, MES, and logistics systems
- Leveraged Amazon S3 for staging and archival
Data Engineering & Automation
- Developed reusable Python ETL scripts with robust scheduling
- Automated ingestion of daily production, order, and inventory metrics
- Ensured data consistency with built-in validation checks
Data Modeling & Performance Optimization
- Modeled data into subject-specific layers for ease of access
- Indexed high-usage tables and applied clustering in Snowflake
- Reduced query latency for downstream dashboards and alerts
Scalability & Future-Readiness
- Established infrastructure to support IoT device integration
- Built baseline for AI/ML-driven insights in next phase
- Created a monitoring layer for pipeline health and usage metrics
Technologies Used
No items found.
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