Enterprise Data Platform Migration to Enhance Scalability and Efficiency in Manufacturing Operations

The client faces difficulties processing large volumes of logistics and production data due to limitations of existing data repositories. Their current setup hampers data integration speed, drives higher operational costs, and restricts timely insights into manufacturing processes. There is a need to consolidate vast data sources into a scalable, cost-effective data platform to improve processing speed and support business growth.

A large multinational manufacturing corporation with extensive logistics and production data management needs seeking to modernize and optimize their data processing infrastructure.

• Migration of existing data from legacy repositories to a centralized, scalable data platform.
• Optimization of data processing workflows to handle a fivefold increase in data volume without compromising performance.
• Implementation of automated data lineage and documentation for enhanced visibility into data provenance.
• Reduction of overall data processing costs with minimal operational cost increase (~10%).
• Enhanced data integration capabilities to support increased data source complexity and volume.
• Establishment of a modular, flexible environment to evaluate resource usage and identify resource-intensive data processes.

• Migration capability from existing data repositories to a modern cloud-based data lake or warehouse.
• Support for cross-platform data transformation and automation (e.g., using data build tools).
• Automated generation and management of data lineage and provenance documentation.
• Deployment of data pipelines for seamless, real-time or batch data transfer using orchestration tools (e.g., data factory or equivalent).
• Dedicated computational environments for resource usage analysis, cost tracking, and performance monitoring.
• Scalability features to accommodate increasing data loads over time without impacting system performance.

• Legacy database systems (e.g., SQL Server or equivalents) for data migration
• Logistics and production data sources
• Data transformation and automation tools
• Monitoring and logging platforms for performance and cost tracking

• Ability to handle at least 5x increase in data volume over regular operation
• System uptime of 99.9% with robust disaster recovery capabilities
• Data security compliance with enterprise standards
• Automated and comprehensive data lineage documentation
• Cost efficiency, maintaining operational expense increase within 10% year-over-year

The migration and modernization of the data platform are expected to significantly enhance operational efficiency by increasing data processing capacity fivefold, reducing costs with only a 10% increase in operational expenses, and accelerating data processing workflows. Additionally, improved data visibility through automated lineage and documentation will support better decision-making and resource optimization over time.