Multicedi modernizes data platform with Microsoft Fabric for faster decisions

Modernizing data management in large-scale retail

Multicedi is a leading retail operator in Italy, managing a network of more than 600 stores that generate billions of point-of-sale transactions every year. In an industry defined by high transaction volumes, complex assortments, and tight margins, the ability to turn data into timely, reliable insights has become critical to supporting decisions related to sales performance, product mix, promotions, and inventory management.

For Multicedi, digital transformation plays a central role in improving operational efficiency and strengthening business governance through a data-driven approach. To support this journey, the company partnered with Advisio, a Microsoft partner with deep expertise in data, analytics, and AI, supporting retail and consumer goods organizations in modernizing large-scale data platforms.

Rethinking the data platform 

Over time, Multicedi's data landscape had grown increasingly complex, with information coming from multiple sources, including stores, distribution centers, purchasing and transfer processes, and administrative and financial systems. 

This complexity introduced several challenges: difficulty consolidating data from heterogeneous sources, fragmented ingestion and normalization processes, delays in making information available to the business, inconsistent data access across stakeholders, and growing demand for timely, reliable analytics across all stores. 

These challenges limited Multicedi's ability to gain a timely, end-to-end view of sales performance and operational trends across its retail network, reducing the effectiveness of decisions related to product mix, promotions, and inventory planning. To support future growth, the company recognized the need to reimagine its data platform, moving toward a modern, scalable architecture designed for advanced analytics and increased responsiveness at store level. 

Unifying and governing data with Microsoft Fabric

Multicedi launched a data modernization initiative built on Microsoft Fabric, establishing a unified foundation to centralize and govern its data estate. By consolidating ingestion, transformation, and analytics on a single platform, Microsoft Fabric replaced fragmented processes with a more streamlined and governable data workflow, improving data consistency, access control, and overall data reliability.

Data from point-of-sale systems and operational sources is ingested using Fabric Data Pipelines and transformed through Fabric Notebooks written in PySpark, enabling parallel processing to efficiently handle large volumes of transactional data. This approach creates curated datasets that support both operational and analytical reporting, while simplifying data ingestion and orchestration and reducing manual effort compared to previous integration processes.

Fabric Spark plays a key role in managing scale, allowing data transformations to run in parallel across massive datasets. Compared to the legacy environment, Spark-based processing in Fabric enabled greater scalability and consistency when handling high-volume retail transactions. As a result, ETL processing times were reduced from approximately six hours to two hours, improving data freshness and enabling more frequent and reliable data refreshes across the retail network.

Scalable analytics and near real-time insights

With the modernized architecture, Multicedi can now support near real-time analytics across its store network, enabling faster visibility into daily sales performance and operational trends. This is critical for the business, as it allows central teams to analyze large volumes of transactional data more quickly, verify the execution and effectiveness of promotions across stores, and identify changes in sales patterns as they occur. Transactional data is stored in SQL Database in Microsoft Fabric, allowing business teams to monitor trends and respond more quickly to changes during the business day. This approach replaced batch-oriented reporting with more timely visibility, supporting operational decisions that previously relied on delayed data.

Insights are delivered through interactive Power BI reports using Direct Lake mode and shared semantic models, ensuring consistent data definitions, role-based security, and self-service access. Direct Lake mode improved report performance while simplifying the analytics architecture, even when working with very large datasets. Faster access to up-to-date information has reduced the time required to analyze sales performance, allowing teams to act on insights during the business day, such as adjusting promotional actions, monitoring store performance, and reacting more quickly to unexpected sales trends, rather than relying solely on end-of-day reports.

Improved access to timely sales data also supported better decisions around product mix, promotion monitoring, and inventory planning, helping teams respond more effectively to changing demand patterns.

This shift enabled business teams to move from retrospective analysis to more proactive monitoring of sales performance and operational indicators.

Making insights more accessible with AI

The modern data platform, with data unified in OneLake, provides a strong foundation for advanced analytics and AI adoption. By centralizing data in OneLake, Multicedi established a single source of truth that improves consistency across analytics, reporting, and AI use cases, enabling a more integrated approach to data-driven decision-making.

“With a unified data platform, we can now analyze large volumes of data more quickly and intuitively, leveraging AI to support everyday business decisions,” stated Livio De Prisco, CTO, Multicedi

Building on this foundation, machine learning models implemented using Fabric Notebooks support the analysis of sales behavior, enabling use cases such as demand forecasting and basket analysis. At the same time, integration with Copilot allows users to explore data using natural language, making insights easier to discover and reducing reliance on technical skills.

Together, these capabilities enable central teams to combine advanced analytics with more intuitive data exploration, improving the quality and timeliness of decisions across retail operations. As a result, insights are no longer confined to specialized teams, but can be more easily explored and shared to support everyday decision-making, even where financial outcomes are still being measured

“Microsoft Fabric allowed us to design a scalable data platform capable of processing billions of retail transactions, while simplifying analytics and enabling AI adoption for business teams, explained Stefano Rossi, CEO, Advisio.

A strong foundation for the future

By adopting Microsoft Fabric, Multicedi has established a modern, unified, and scalable data platform that transforms large volumes of data into meaningful business value.

Beyond technical improvements, the transformation delivered tangible business value by shortening analysis cycles, improving operational responsiveness, and supporting more informed decision-making across the retail network. The new foundation also positions Multicedi to further extend advanced analytics and AI initiatives in a highly competitive retail environment.

Discover more about Multicedi on LinkedIn.