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Enterprise Data Migration for Engineering-Focused Tech Company
  1. case
  2. Enterprise Data Migration for Engineering-Focused Tech Company

Enterprise Data Migration for Engineering-Focused Tech Company

https://soltech.net
Manufacturing
Supply Chain
Logistics

Challenge of Legacy Data Management Hindering Operational Efficiency

The client faces the challenge of managing and migrating over 15 years’ worth of complex project data stored in outdated, custom-built database systems. These legacy systems impede data accessibility, increase maintenance costs, and hinder project management, warranty support, inventory, and parts management. The transition to a modern system is critical to improve operational efficiency, support automation, and enable digital workflows, all while ensuring data integrity during migration.

About the Client

A mid-sized engineering-oriented manufacturing company specializing in custom products, requiring a robust system for managing extensive project data and supporting digital transformation efforts.

Key Goals for Data Modernization and Operational Enhancement

  • Successfully migrate and consolidate over 15 years of project data from legacy systems to a new, scalable platform supporting automation and smart workflows.
  • Ensure data accuracy and integrity throughout the migration process to maintain support, inventory, and warranty management capabilities.
  • Decommission outdated systems upon successful migration, leading to cost reductions and streamlined data management.
  • Complete the project within the scheduled timeline and budget, minimizing operational disruptions.
  • Enhance data accessibility and searchability to improve project management and customer support efficiency.

Core Functional Requirements for Data Migration System

  • Comprehensive data extraction from legacy database sources, including custom-built apps.
  • Data cleansing and validation routines to correct inconsistencies and resolve quality issues.
  • Data merging, transformation, and structuring aligned with new system schemas.
  • Relational mapping of files and associated data to maintain context and traceability.
  • Minimal operational disruption through phased migration and coexistence with legacy systems.
  • Automated backup and validation processes to ensure data integrity.

Technological Stack and Architecture Preferences

ETL tools supporting comprehensive data extraction and transformation
Relational database platforms supporting automation and smart workflows
Data cleaning and validation frameworks
Secure, scalable cloud-based or on-premise infrastructure

External System Integration Needs

  • Legacy custom-built applications housing historical data
  • New database platforms supporting RPA and automation features
  • Existing support and inventory management tools

Non-Functional System Requirements and Performance Metrics

  • High data accuracy with a target of 99.9% validation success
  • Migration completion within a timeline of estimated 3-6 months
  • Data security and compliance with industry standards
  • System scalability to handle ongoing data growth
  • Minimal operational downtime during migration

Business Outcomes and Benefits of the Data Migration Project

By successfully migrating and consolidating extensive project data onto a modern platform, the client is projected to reduce maintenance costs associated with legacy systems, improve data accessibility and operational efficiency, and support automation initiatives. The project aims for a seamless transition with minimal disruption, positioning the company for enhanced project management, support, and future growth.

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