Case StudyOngoingData warehouse on Microsoft Fabric for a 200+ pharmacy chain
Magistra a.s. operates more than 200 pharmacies across the Czech Republic alongside its own e-shop. We are building a central data warehouse on Microsoft Fabric β integrating data from individual pharmacies, physician and specialty data, the e-shop, and further systems into a unified platform for reporting and analytics.
200+
pharmacies integrated
unified data view
MS Fabric
unified analytics platform
one tool for everything
Real-time
performance reporting
instead of manual reports
360Β°
customer view
online and offline channels
Data from 200+ pharmacies, an e-shop, and external systems β siloed, with no unified view
A network of more than 200 pharmacies generates enormous volumes of data β sales, inventory, prescriptions, customers. On top of that come data from the proprietary e-shop, information about physicians and their specialties, and a range of other systems. Each source lived in its own silo. Without a central data warehouse, meaningful reporting, branch performance comparisons, or deeper data analyses were not feasible.
Pharmacy data
fragmented, in separate systems
Performance reporting
manual, slow, unreliable
E-shop data integration
missing entirely
Data analytics
practically impossible without a DWH
Challenge
connecting all data sources into a single analytics platform
a unified data warehouse
Microsoft Fabric as the central data platform
We are designing and building a data warehouse on Microsoft Fabric β Microsoft's modern unified analytics platform. We integrate data from all sources, ensure cleansing and transformation, and deliver reporting and analytical tooling.
Microsoft Fabric β unified analytics
A data warehouse built on Microsoft Fabric combines data integration, lakehouse storage, transformations, and reporting in a single platform β without the complexity of managing separate tools.
Pharmacy data ingestion
Automated ETL pipelines ingest data from individual pharmacies β sales, inventory, prescriptions, and customer data β and centralise them in the data warehouse.
Physician and specialty data integration
Integration of external data on physicians, their specialisations, and areas of expertise enables prescription behaviour analyses and identification of business opportunities.
Proprietary e-shop integration
Data from the online sales channel is combined with data from physical pharmacies β a unified view of the customer across all channels.
Additional system integrations
The open data warehouse architecture allows further data sources to be connected incrementally according to business priorities.
Reporting and data analytics
Pharmacy performance reporting, sales analyses, customer segmentation, trend analyses, and ad-hoc querying over centralised data.
Solution Architecture
The data platform is built on Microsoft Fabric β data is ingested from heterogeneous sources (pharmacy systems, e-shop, external registries), passes through ETL transformations, and is stored in the lakehouse layer. Power BI provides reporting and self-service analytics.
Data Sources
200+ Pharmacies
POS, inventory, prescriptions
E-shop
orders, customers
Physicians & Specialties
external registries
Additional systems
expanded incrementally
β
Microsoft Fabric
Data Factory
ETL pipelines
Lakehouse
central storage
Power BI
reporting & analytics
β
Integrations
Results
Central data warehouse
All data from pharmacies, the e-shop, and external sources in one place β the end of data silos.
Automated ETL pipelines
Regular ingestion and transformation of data from all sources without manual intervention.
Pharmacy performance reporting
Branch performance comparisons, sales trend analyses, anomaly identification, and opportunity discovery.
Prescription behaviour analytics
Linking physician and specialty data with sales data enables entirely new business analyses.
Unified customer view
Data from physical pharmacies and the e-shop connected into a single customer profile.
Scalable architecture
An open platform ready for the incremental addition of new data sources and analytics use cases.
Technologies
- Microsoft Fabric
- Power BI
- Azure Data Factory
- Lakehouse
- SQL
- Python
- ETL pipelines
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