Healthcare · Regulatory · Data & Analytics
Microsoft Azure Microsoft Fabric Medallion Architecture Power BI PHIPA Compliance RBAC
Client Overview.
Our client, an Ontario-based Health Professional Regulatory Body, had data spanning multiple SaaS platforms for registrant regulation, public protection, policy development, and stakeholder communications, manual reporting, and no governance. Operating under the Regulated Health Professions Act (RHPA), unified intelligence directly translates to compliance adherence for the PHIPA (Personal Health Information Protection Act) and more efficient operations for them. But in the absence of unified data, their teams were spending more time on inefficient processes for manual data extraction and conflicting KPIs— far from centralized governance at scale.
Business Challenge.
Businesses in regulated industries need unified data from all sources not just for governance and compliance, but also reliable decision-making, team alignment, and operational efficiency. But their existing process relied on fragmented data from multiple SaaS platforms, which delayed decisions, created compliance loopholes, and put operational capacity at risk. Key challenges included:
Delayed decisions with inefficient manual reporting requiring teams to download source exports, transform data in Microsoft Excel, and upload to Tableau.
Fragmented insights from existing Tableau dashboards disconnected from automated pipelines, data from multiple SaaS platforms.
Risked business continuity with KPI computation logic embedded in individual Excel files that limited team members could access.
Absence of any organization-wide governance standards, data catalog, lineage documentation, access control framework, and field-level PII classification for ensuring data access to the right people and meeting PHIPA requirements.
Proportional staff overhead while adding new data sources or expanding analytics at scale.
Our Approach & Solution.
Algoscale implemented the Medallion Architecture (Bronze / Silver / Gold) on Microsoft Azure and Microsoft Fabric, organizing data into three distinct layers — each serving a specific purpose in the data lifecycle to facilitate data unification, data integration from all source systems, and establishing centralized governance for analytics at scale.
Raw Ingestion
Transformation
Analytics-Ready
Key Components.
Source Systems Integration
We integrated data from all source systems, including Thentia, the registrant database for all practitioner data, Clobba, the MS Teams call analytics and call centre data, to GA4 web analytics, Hootsuite for social media analytics, Mailchimp for emails, Martus for finance and KnowBe4 for IT security/phishing in Full Load or Incremental load types.
Ingestion Architecture
Each source follows one of the two production-grade ingestion patterns:
Pattern A SFTP / CSV.
Pattern B REST API.
Production-Grade Schema Drift Strategy
A schema-drift strategy, particularly for data sources like Thentia and Clobba— known for unannounced schema changes:
Detection.
Silver Layer Protection.
File Naming Failures.
Remediation Responsibility.
KPI Dashboards
We designed, built, and validated domain-based KPI dashboards, each following the Bronze-Silver-Gold pipeline:
We delivered 131 KPI definitions— all documented in the KPI register with business owner sign-off.
- Registrations & Regulatory
- Investigations & Personal Conduct
- Communications & Social Media
- Finance
- Call Centre Operations
- Compliance & Security Awareness
Production-Grade Pipeline Orchestration
Orchestration.
All data pipelines are orchestrated using Microsoft Fabric Data Factory with production-level reliability and error handling, with all 7 ingestion pipelines triggering on a daily schedule, pipeline failures generating immediate P1 alerts, and a daily pipeline health summary report delivered to the CMTO IT distribution list by 07:00 EST.
PHIPA Compliance Architecture and Role-based Access Control (RBAC).
Full PHIPA & PIPEDA Compliance Architecture
Our platform was fully designed to meet PHIPA and PIPEDA obligations, including AES-256 encryption at rest applied natively across all OneLake storage, all credentials and password stored in Azure Key Vault, automated data catalog scanning with Microsoft Purview, column-level lineage, complete audit logging, and all Azure sources provisioned exclusively in the Canada Central region.
We designed and implemented a RBAC framework for our client's 61 named users across six defined roles. Row-Level Security is applied in the Power BI semantic model for domain-restricted roles using USERPRINCIPALNAME() matched against department fields.
Serverless Cost Optimization
Cost Design.
We designed the platform for cost efficiency and eliminated all idle compute, with Microsoft Fabric Data Factory billing only when pipelines are executing, OneLake lifecycle management policies applying tiered storage based on data age per layer, and Fabric Lakehouse SQL endpoint using serverless billing — compute capacity scales automatically with workload demand.
Data Quality and Validation
Quality.
A comprehensive data quality framework was implemented across all Medallion layers with every rule formally documented in the Data Quality Rule Catalogue, with results accessible to relevant stakeholders via Power BI or direct query.
Impact & Results.
All 7 SaaS data sources integrated into a single Azure Data Lakehouse to replace siloed workflows with governed pipelines.
Role-based, self-service, and daily automated Power BI dashboards replace manual reporting.
Manual effort eliminated for Finance and Operations teams to focus on primary tasks.
Board-level dashboard refresh reduced from 1–2 day manual lag to same-day automated delivery with sub-5-second load times in Power BI.
Fabric Data Factory orchestration ensures daily automated refresh by 06:00 EST with immediate alerting on failure.
Advanced from Analytics Maturity Level 1.5 (Ad-hoc/Developing) to Level 3 (Defined) — with a documented roadmap toward Level 4 (Managed) in subsequent phases.
Conclusion.
Algoscale helped an Ontario-based Health Professional Regulatory Body replace fragmented, manual reporting processes into a centralized, governed Azure Data Lakehouse built for compliance, scalability, and operational efficiency. By integrating multiple SaaS platforms into a unified analytics ecosystem with automated pipelines, role-based access control, and PHIPA-aligned governance, we helped the organization achieve faster and reliable decision-making and reduce operational overhead, while empowering their teams to focus on core competencies.
As a leading Data Consulting and AI Services Company, Algoscale combines cloud-native engineering, governance expertise, modern analytics architecture, and proprietary battle-tested frameworks to help regulated organizations build secure, scalable, and insight-driven data platforms that support compliance, business continuity, and data-driven growth.
Project Details.
