About Home Hardware
Home Hardware Stores Limited is one of Canada's largest home improvement retailers, operating a large network of independently owned stores across the country.
The organization manages a highly complex retail environment that includes store operations, supplier management, inventory systems, SKU-level reporting, e-commerce activity, and enterprise operational data.
Because stores operate independently while reporting into a centralized organization, maintaining consistent and trusted enterprise data across all systems is both critical and operationally challenging. As the business expanded its digital operations and supplier ecosystem, the need for a unified and scalable data foundation became increasingly important.
The Business Challenge
Home Hardware's operational and sales data was spread across several disconnected legacy systems. Oracle ERP handled financial and operational workflows. E-commerce platforms managed online transactions independently. Point-of-sale systems stored in-store transaction data separately.
None of these environments shared a unified enterprise data model. As a result, building enterprise-wide reporting required significant manual profiling, mapping, reconciliation, and ETL development.
The organization wanted a centralized view of:
- Sales performance
- Store operations
- SKU-level analytics
- Supplier activity
- Cross-channel reporting
However, using traditional engineering methods, the projected timeline for modernization was estimated at approximately 12 months. That timeline did not align with the organization's operational priorities or business growth plans.
Legacy Environment
Before modernization, the environment included:
- Oracle ERP systems supporting financial and operational data
- Separate e-commerce transaction platforms
- Isolated point-of-sale systems across physical retail operations
- No centralized enterprise data model connecting systems together
- Heavy manual effort required for data profiling and integration
- Long ETL development timelines using traditional engineering methods
- No unified reporting framework across retail channels
The fragmented structure made enterprise reporting slow, resource-intensive, and difficult to scale.
Why Change Was Needed
Without a centralized and trusted analytics foundation, Home Hardware struggled to maintain consistent reporting across physical stores, e-commerce operations, and supplier networks. SKU-level reporting and supplier analysis required manual reconciliation across systems, which created delays and operational inefficiencies.
As the business expanded digitally and operational complexity increased, the limitations of the fragmented environment became more difficult to manage. The organization needed a scalable platform capable of supporting enterprise-wide visibility across all retail and operational channels.
The OpenOntos Approach
OpenOntos modernized Home Hardware's data environment by building a unified Microsoft Fabric Lakehouse that consolidated store, SKU, supplier, ERP, e-commerce, and POS data into a centralized analytics platform.
The implementation used AI-assisted profiling and automated pipeline generation to dramatically accelerate the delivery timeline. What was originally projected as a 12-month initiative was completed in just 90 days.
The engagement also delivered two enterprise-ready use cases focused on:
- Sales performance reporting
- Store performance analytics
The implementation followed a Medallion Architecture model (Bronze, Silver, Gold) within Microsoft Fabric's OneLake environment to ensure governance, scalability, and structured data quality management.
Migration & Modernization Strategy
The modernization strategy focused on unifying all retail and operational data into one governed and scalable analytics foundation. Key implementation activities included:
- Ingesting Oracle ERP, e-commerce, and POS data into Microsoft Fabric Lakehouse
- Implementing Bronze, Silver, and Gold Medallion Architecture layers
- Applying AI-assisted profiling to identify schema relationships and transformation requirements
- Automating ETL and pipeline generation to reduce manual engineering effort
- Standardizing SKU and supplier definitions across all operational channels
- Delivering two production-ready Gold Layer use cases for sales and store performance reporting
The overall goal was to simplify integration complexity while enabling faster enterprise reporting.
AI & Automation Role
AI-assisted automation played a major role in accelerating project delivery. OpenOntos used AI-powered profiling to rapidly analyze Oracle, e-commerce, and POS schemas, identifying relationships and data structures that would traditionally require weeks of manual engineering analysis.
Automated pipeline generation then created the ETL logic required to move data through the Medallion Architecture layers. This significantly reduced the amount of hand-coded ETL development required while improving delivery speed and operational consistency. The combination of AI-driven analysis and automation became one of the primary drivers behind the 4× faster implementation timeline.
Technical Transformation Highlights
The implementation delivered several major technical improvements across Home Hardware's analytics environment:
- Three disconnected legacy systems unified into a single Microsoft Fabric Lakehouse
- Bronze, Silver, and Gold Medallion Architecture implemented for structured data governance
- Standardized SKU and supplier definitions established enterprise-wide
- 360-degree sales visibility created across ERP, e-commerce, and POS systems
- Automated and governed pipelines replacing manual ETL development
- Enterprise-ready Gold Layer analytics models available from day one
The final environment created a much cleaner and more scalable analytics foundation for enterprise reporting.
Business Outcomes
The modernization delivered measurable operational and business improvements:
- Full implementation completed in 90 days instead of the projected 12 months
- 80% reduction in manual ETL and integration effort
- Unified sales and operational reporting across all channels
- Enterprise-wide standardization of SKU and supplier definitions
- Faster and more reliable enterprise analytics delivery
- Foundation established for inventory optimization and supplier performance tracking
Operational Impact
Merchandising and operations teams gained a centralized and trusted view of store and sales performance across both physical and digital retail channels. SKU-level reporting that previously required extensive reconciliation across systems became a routine enterprise reporting process.
Supplier visibility also improved significantly because standardized definitions allowed teams to compare and analyze operational performance consistently across channels. The accelerated delivery timeline also allowed business capabilities originally expected much later in the roadmap to become available within the same operational quarter.
Key Benefits Achieved
- Unified Microsoft Fabric Lakehouse replacing disconnected legacy systems
- Centralized sales and operational reporting across all retail channels
- Significant reduction in ongoing engineering and ETL maintenance effort
- Scalable Medallion Architecture supporting future growth and expansion
- Faster and more reliable enterprise reporting capabilities
- Strong foundation for inventory analytics, supplier intelligence, and customer personalization initiatives
Conclusion
Home Hardware's modernization project demonstrates how AI-assisted automation can dramatically accelerate enterprise data transformation without compromising governance or scalability. By replacing months of manual profiling and ETL development with AI-driven analysis and automated pipeline generation, OpenOntos helped compress a 12-month initiative into a fully operational 90-day delivery.
The organization now has a scalable and governed analytics platform capable of supporting enterprise-wide operational visibility, faster reporting, and future retail intelligence initiatives across both physical and digital channels.