Anonymized engagement summary: Azure data warehouse and Power BI dashboards for a medical device manufacturer's sales and finance reporting (2025)
Anonymized engagement summaryMedical device manufacturer · 2025
Opening answer. In 2025 EPC Group was engaged by a medical device manufacturer to build an Azure data platform — Data Factory pipelines, Data Lake Storage for staging and Synapse Analytics for reporting — that loads SQL Server and Excel data daily. The work also covers dimensional models for the company's KPIs and four to five Power BI dashboards with row-level security. During the engagement the client shared its source workbooks with EPC Group: sales against quota, daily and international sales, product-line gross margin, repair orders and a pricing and inflation calculator.
This is an anonymized engagement summary published under EPC Group's anonymized-engagement rule: the client is not named, no commercial terms are published, and every statement is EPC-reported. Named, documented engagements are in the Evidence Center.
Problem and scope
| Item | Scope |
|---|---|
| Organization | A medical device manufacturer |
| Situation | Sales and finance reporting held in SQL Server and large Excel workbooks |
| Objective | Integrated, transformed data on Azure that supports business-critical reporting, with self-service analytics and near-real-time reporting through Power BI |
| Architecture | Azure Data Factory for ingestion and data flows, Azure Data Lake Storage for staging, Azure Synapse Analytics for transformation and reporting |
| Data | SQL Server and Excel sources, loaded by daily incremental schedules |
| Modelling | Star and snowflake dimensional models for the company's KPIs, with data quality, consistency and integrity validated through the pipeline and transformation logic documented |
| Reporting | Four to five interactive Power BI dashboards on Synapse, with row-level security and self-service analytics |
| Close-out | End-to-end and performance testing; architecture designs, data definitions and operational runbooks; knowledge transfer; production deployment on automated schedules; hyper-care after go-live |
Not reported: data volumes, the number of report users, the go-live date and any measured change in reporting time or accuracy.
Approach and artifacts
Assess the sources and the compliance needs first. Discovery evaluates the existing SQL Server and Excel sources: architecture, data quality, constraints, and an inventory of tables, schemas and file structures to size the work. It checks the readiness of the Azure services and sets data-security and compliance protocols for handling sensitive data, including any regulatory requirements that affect the design.
A roadmap before a build. The first deliverable is a data-warehouse roadmap tailored to the company: goals and technical requirements, challenges and opportunities in the current data, and a step-by-step plan for preparing both the source systems and Azure.
Pipelines, models, then dashboards. Ingestion pipelines land data in the lake and Synapse on a daily incremental schedule. Cleansing and transformation run in Synapse and Data Factory data flows. Dimensional models carry the KPIs, and the Power BI dashboards sit on top, secured by role.
Leave the team able to run it. Runbooks, data definitions and transformation logic are documented. Hands-on sessions train the finance and technical teams to use the dashboards, use Synapse for self-service analysis, and maintain and troubleshoot the pipelines.
What EPC Group delivered and what is not claimed
| Claim | Basis | Status |
|---|---|---|
| The company contracted EPC Group for an Azure data warehouse and Power BI dashboards | EPC engagement record | Contracted (EPC-reported) |
| The client supplied its source workbooks for the build | Client-provided files on file (2025) | On file (EPC-reported) |
| Dashboards delivered, accepted, or in production; any measured result | Not reported | Not claimed |
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Last updated by Errin O'Connor, Founder & Chief AI Architect, EPC Group
Related service: Azure Data Lake + Power BI Architecture
Author: Errin O'Connor, Founder & Chief AI Architect, EPC Group · Published October 25, 2026 · Project alias EPC-2025-ANON-MEDDEV-AZDWPBI · Published under the anonymized-engagement rule.