About the Ontario Medical Association
The Ontario Medical Association (OMA) represents more than 43,000 physicians across Ontario, supporting healthcare professionals through advocacy, member services, policy support, professional development, and operational programs.
As one of the largest and most operationally complex professional associations in the province, the OMA manages large volumes of member, policy, engagement, insurance, and case management data across multiple departments and systems.
Over time, the organization accumulated data across several legacy platforms that worked independently but lacked a unified structure when viewed together at the enterprise level.
The Business Challenge
Before modernization, the OMA's data environment was fragmented across disconnected systems, spreadsheets, and legacy platforms. There was no centralized data lake, governance framework, or analytics foundation connecting organizational reporting across departments.
Critical business functions such as member engagement, sales and revenue reporting, communications tracking, and case management relied heavily on manual reporting processes and spreadsheet-based workflows.
The challenge was not simply upgrading technology. The organization needed a trusted and scalable data foundation that could support both immediate reporting requirements and future AI and automation initiatives. Traditional project estimates projected approximately one year to complete the modernization effort. The OMA needed a faster and more sustainable approach.
Legacy Environment
Prior to the implementation, the OMA's environment included:
- Four primary legacy source systems containing millions of records
- Spreadsheet-driven reporting workflows across multiple teams
- No centralized data lake architecture
- No enterprise governance or cataloging layer
- Limited automation across reporting and analytics processes
- Manual reconciliation and data preparation workflows that required significant operational effort
The lack of centralized governance and automation created delays, inconsistencies, and growing operational overhead.
Why Change Was Needed
Leadership teams needed reliable enterprise reporting across marketing, engagement, sales, revenue, and operational case management without depending on manual data assembly.
The organization also wanted to establish a foundation for future AI and automation capabilities, but that required governed, structured, and analytics-ready data that simply did not exist in the current environment. The existing approach could not scale with the organization's operational and reporting needs.
The OpenOntos Approach
OpenOntos approached the engagement as a complete greenfield modernization initiative. The platform was built from the ground up using Microsoft Fabric's OneLake architecture, creating a centralized and governed enterprise data foundation for the organization.
To accelerate delivery, OpenOntos used AI-assisted data profiling and automated model generation to significantly reduce the amount of manual engineering work typically required in enterprise data projects.
At the same time, a Medallion Architecture approach (Bronze, Silver, Gold) ensured data quality, consistency, and governance improved progressively across every layer of the platform. The entire environment was integrated with Microsoft Purview, providing governance, cataloging, and compliance visibility from the beginning of the project.
Most importantly, the platform was delivered with a lean engineering team of only three people instead of the much larger team size traditionally required for similar implementations.
Migration & Modernization Strategy
The engagement covered the full lifecycle of the data platform implementation, from ingestion through production-ready analytics models. Key implementation activities included:
- Building a Bronze Layer for raw ingestion from all four source systems
- Creating standardized and cleansed Silver Layer models with unified definitions
- Delivering 16 production-ready Gold Layer use cases within the first 60 days
- Integrating Microsoft Purview for governance, cataloging, and compliance readiness
- Replacing spreadsheet-driven processes with automated data pipelines
- Establishing a scalable architecture capable of supporting future AI and automation initiatives
AI & Automation Role
AI-powered automation played a major role in reducing project timelines and engineering effort. Instead of manually profiling schemas and writing transformation logic from scratch, OpenOntos used AI-assisted profiling and automated model generation to accelerate the identification of source structures and analytical relationships.
This dramatically reduced the time required to move use cases into production. As a result, the organization was able to deploy 16 production-ready Gold Layer use cases within just 60 days – a pace that would have been difficult to achieve using conventional engineering methods alone.
Technical Transformation Highlights
The initial Gold Layer implementation covered several high-value operational and reporting domains.
Marketing & Engagement:
- Automation activity monitoring
- Campaign performance reporting
- Email engagement and frequency analysis
- Journey and workflow tracking
- Subscriber and communication analytics
Sales & Revenue Intelligence:
- Multi-layered sales and revenue reporting models
- Enterprise visibility into financial and operational performance
Case Management Analytics:
- Workload tracking and reporting
- Resolution and operational analysis
- Case management performance visibility
The final environment created a fully governed and analytics-ready enterprise platform built on Microsoft Fabric OneLake.
Business Outcomes
The implementation delivered significant operational and delivery improvements across the organization:
- Delivery timeline reduced from approximately 1 year to 4 months
- More than 6,000 engineering hours saved through AI-assisted automation
- Engineering team size reduced from 9 engineers to 3
- 16 production-ready Gold Layer models delivered within 60 days
- Full Microsoft Fabric OneLake platform operational in 4 months
Operational Impact
Teams across marketing, membership, operations, finance, and case management moved away from spreadsheet-based reporting and into a governed, automated analytics environment. Reports that previously required extensive manual effort could now be generated automatically with trusted and centralized data.
The integration of Microsoft Purview also ensured governance and compliance were built directly into the architecture rather than added later as separate processes. Most importantly, the organization now has a scalable foundation capable of supporting future AI and automation initiatives across multiple operational domains.
Key Benefits Achieved
- Complete enterprise data lake and governance platform built in 4 months
- Governed Microsoft Purview environment with cataloging and compliance visibility
- AI-ready analytics foundation supporting future automation initiatives
- Significant reduction in manual reporting and reconciliation effort
- Scalable and maintainable architecture manageable by a lean internal team
- Faster and more reliable operational reporting across all business functions
Conclusion
The Ontario Medical Association's modernization project demonstrates what is possible when AI-assisted automation is combined with a practical and well-governed enterprise data strategy. In just four months, OpenOntos delivered a fully operational Microsoft Fabric platform that the organization had originally estimated would take nearly a year to complete.
The result was more than a technology upgrade. The OMA now operates on a governed, scalable, and AI-ready data foundation that gives teams across the organization faster access to trusted information while positioning the association for future automation and intelligence initiatives.