Rebuilding a Legacy Database for a Commercial Window Manufacturer

Mid-market, 50–150 employees Greater Toronto Area Fixed-term project

A 30-year fenestration manufacturer's outdated backend was slowing operations and driving up costs. BALANCED+ rebuilt their data access layer from the ground up, on time and under budget.

With nearly three decades of experience in the fenestration industry, this company has established itself as a recognized leader in high-rise construction and renovation. They specialize in fabricating commercial and residential thermal aluminum window products, integrating architectural metal and glass for some of the region’s most demanding building projects.

Operating at this scale requires tight coordination between sales, production, and inventory, making reliable, well-structured backend systems essential to day-to-day operations.

Despite their long track record and industry reputation, the company’s internal systems hadn’t kept pace with their growth. Their existing database infrastructure was built on legacy code that had become increasingly difficult to maintain, extend, or integrate with modern tools. What had once been functional was now a bottleneck, slowing down processes across inventory management, sales tracking, and production coordination.

The company needed more than a patch. They needed a complete rebuild of their data access layer, with a clean architecture that could accommodate data from multiple internal and external sources while supporting future functionality without accumulating further technical debt.

Legacy database code was creating inefficiencies across inventory, sales, and production workflows.
The existing data structure couldn't support integration with external data sources or modern tooling.
Mounting technical debt was increasing operational costs and limiting the team's ability to scale.
No formal documentation existed for the current database structure, making rebuilding high-risk without proper analysis.

BALANCED+ assigned a dedicated Project Manager and applied a structured waterfall methodology to ensure every phase was clearly scoped, documented, and signed off before development began. This approach was well-suited to the project’s fixed requirements and the client’s need for predictability and auditability throughout the engagement.

JIRA was used to maintain detailed logs of functionality, backlogs, and release structure, while project time was tracked to ensure the engagement stayed on budget. The result was a fully documented, normalized database with a modern codebase, delivered without surprises.

Discovery & Requirements Documentation

Conducted a thorough business process analysis to document existing workflows, pain points, and requirements before any architecture decisions were made.

Database Architecture Design

Designed a new inventory object model with full normalization, an Entity Relationship Diagram, and an optimization plan aligned to the company's operational data flows.

Microsoft SQL Server & Entity Framework Build

Constructed the new data access layer using Microsoft SQL Server and Entity Framework, configured to ingest data from external research sources, sales tracking tools, and internal production systems.

Integration & Workflow Mapping

Developed detailed work-flow diagrams and ensured the new database structure connected cleanly with existing operational systems across departments.

Delivery & Handoff

Delivered a complete documentation package alongside the new codebase, giving the internal team full visibility into the architecture and a clear foundation for future development.

The project was completed on time and under budget, a meaningful outcome given the complexity of the rebuild and the lack of existing documentation. The new data access layer replaced years of accumulated technical debt with a clean, normalized database architecture built on Microsoft SQL Server and Entity Framework.

With a fully documented codebase and a modern architecture designed for extensibility, the manufacturer now has a foundation that supports integration with external data sources, scales with their operations, and can be maintained and extended by their internal team going forward.