- Industry: Digital Platforms & Technology
- Service Pillar: Cloud & Infrastructure → Cloud Migration
Executive Summary
A global manufacturing company faced performance limitations and high maintenance costs with its legacy on-premise data warehouse. To achieve agility and scale, the organization engaged Mindmap Technologies to modernize its data platform and migrate workloads to the cloud. The new architecture enabled faster data processing, reduced operational costs, and established a foundation for advanced analytics and AI initiatives.
Problem Overview
- On-premise data warehouse struggling to scale with growing data volumes.
- Complex ETL jobs causing latency and overnight batch failures.
- Limited analytics capability due to hardware and licensing constraints.
- High total cost of ownership (TCO) for infrastructure and maintenance.
Our Solution
- Performed assessment of existing workloads and identified migration readiness gaps.
- Executed phased migration of data warehouse to a modern cloud-based platform.
- Refactored legacy ETL processes into ELT pipelines using cloud-native orchestration.
- Implemented real-time change data capture (CDC) for incremental updates and reporting.
Technologies Used
Azure Synapse, Snowflake, Airflow, Azure Data Factory, Power BI, Databricks, Terraform
Key Outcomes
01
Reduced ETL processing time by 60%, improving data availability for analytics.
02
Enabled near-real-time dashboards for production and supply chain insights.
03
Lowered storage and compute costs by 35% through cloud optimization.
04
Established a scalable foundation for predictive analytics and AI integration.