Technology Strategy And Data Analytics Solution For Multi Radiance Medical Company

Multi Radiance Medical is a leading medical device manufacturer specializing in therapeutic laser technology. With over 20 years of experience, they provide innovative solutions for pain relief, rehabilitation, and sports medicine.

• End-to-end data strategy developed for unified analytics across CRM, ERP, and product sources
• Scalable data warehouse created using Azure Synapse for structured and unstructured data
• Automation of manual data aggregation processes via Azure Data Factory
• Executive dashboards and KPI tracking enabled in Power BI
• Significant improvement in operational visibility and strategic planning

Multi Radiance Medical faced inefficiencies due to manual data collection and siloed reporting. Data from ERP, CRM, and various operational systems was stored across inconsistent formats, often requiring time-consuming consolidation and manual cleanup for reporting. This fragmented landscape slowed down decision-making and created barriers to accurate business insights.

The company needed a centralized and automated solution to integrate structured and unstructured data from multiple departments and systems, and present it in a format that business users could explore in real time. A cloud-native architecture was critical for scalability and future-proofing, with a strong focus on security, performance, and maintainability.

• 1 Azure Data Engineer (ETL pipelines, data lake integration)
• 1 BI Developer (Power BI dashboards, data modeling)
• 1 Solution Architect (Azure Synapse design, architecture governance)
• 1 Project Manager (requirements gathering, delivery tracking)

Softellar designed and delivered a full-scale cloud analytics platform that addressed both the strategic data needs and operational inefficiencies at Multi Radiance Medical. The objective was to consolidate data from ERP, CRM, and marketing systems into a centralized and high-performance data architecture in Microsoft Azure, enabling automated pipelines, scalable reporting, and deep business insights.

The entire solution was cloud-native and modular, allowing for extensibility and future integration of AI models or third-party analytics tools. Our focus was not only on ingestion and warehousing but also on empowering business users with flexible visualization capabilities and intuitive interfaces.

Azure Synapse-Based Data Warehouse

At the heart of the platform, Softellar implemented a robust data warehouse using Azure Synapse Analytics. This served as the central repository for both structured and semi-structured data, designed with star schema principles to support efficient querying across sales, product usage, and customer interaction data. The system included dedicated SQL pools and partitioned tables to ensure performance even under large workloads. Schema designs were aligned with key business domains such as finance, operations, and marketing to support domain-specific analytics.

Azure Data Factory ETL Pipelines

We created reusable and parameterized data pipelines in Azure Data Factory (ADF) to ingest, normalize, and transform data from multiple internal systems and external providers. Each pipeline featured built-in monitoring, retry policies, and logging via Azure Monitor. Data lineage was preserved to ensure traceability, and complex business rules - such as currency conversion or customer segmentation - were embedded within the transformation logic. Pipelines were scheduled for daily and weekly runs depending on business needs.

Azure Data Lake for Raw and Staging Storage

All raw, historical, and staging data was offloaded to Azure Data Lake Storage Gen2. This allowed the team to archive large CSV exports, unstructured logs, and third-party files without performance trade-offs. The lake served as a persistent backup source and enabled advanced analysis down the line. Folder hierarchies were designed to support data lifecycle policies and security boundaries per business unit.

Power BI for Business Intelligence

The front-end of the platform was built using Power BI, enabling business users to interact with their data via prebuilt dashboards, ad-hoc queries, and custom reports. Dashboards were created for finance, sales, and product teams - with visuals like KPI cards, DAX-based dynamic indicators, drill-down filters, and AI-driven Q&A interfaces. Row-level security (RLS) was configured to control visibility by department, and Power BI Workspaces were used for versioned report sharing and collaboration.

Security & Governance Layer

A secure data access model was implemented using Azure RBAC and Power BI service roles. Sensitive data - such as patient interactions and financials - was encrypted both in transit and at rest. Access to specific datasets and reports was governed by user roles, business unit, and location. Audit logs were enabled for compliance and platform transparency.

Softellar delivered the solution in four focused stages, ensuring incremental value and low risk:

1. Strategy & Architecture Design
   Assessed current reporting processes and pain points
   Defined data architecture principles and Azure-based target state
   Designed security, retention, and access governance model
2. Data Ingestion Setup
   Developed ETL flows in Azure Data Factory
   Set up source connectors, schema mapping, and staging environments
   Created monitoring and alerting dashboards for data pipeline health
3. Data Warehouse and Lakehouse Integration
   Built Synapse-based schema optimized for analytics
   Consolidated operational and marketing datasets
   Integrated raw file storage in Azure Data Lake for historical reference
4. Visualization & Training
   Delivered user-friendly Power BI dashboards
   Enabled drill-through reports and natural language querying
   Provided documentation and walkthrough sessions for key users

The Azure-powered analytics platform enabled Multi Radiance Medical to modernize their reporting stack and unlock deeper operational intelligence. With all key data sources unified, decision-makers could identify bottlenecks, track performance metrics, and detect anomalies in real time.

Business Outcomes

• Eliminated time-consuming manual data preparation
• Improved executive decision-making with unified views across departments
• Enabled proactive strategy adjustments using near real-time KPIs
• Identified high-performing products and market segments faster

Technical Outcomes

• Built scalable, cloud-native data infrastructure with low maintenance
• Integrated CRM and ERP sources into a centralized Synapse model
• Automated 90% of manual data workflows using Azure Data Factory
• Enabled self-service reporting for 5+ departments with Power BI

"Thanks to the expertise and dedication of the team at Softellar, we were able to take our data management to the next level. Their innovative solutions helped us streamline our processes and gain valuable insights that have positively impacted our business."

Max Kanarsky

CEO, Multi Radiance Medical

Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, Power BI, SQL