Exponentia.ai

The client relied on a legacy SQL Server data warehouse that could not scale to support multi-channel retail analytics. High infrastructure maintenance costs and slow reporting cycles limited timely access to inventory and sales insights across the retail network.

Exponentia implemented a Microsoft Fabric Lakehouse using a Medallion architecture (Bronze, Silver, and Gold) on OneLake. Data Factory pipelines were developed to ingest data from POS, eCommerce, ERP, and loyalty systems, while Power BI semantic models running in DirectLake mode enabled near real-time inventory and sales analytics across the enterprise.

The client's Teradata-based enterprise data warehouse was approaching end-of-life, resulting in high licensing costs and limiting the analytics team's ability to support new machine learning and Generative AI use cases. The organization required a modern data platform that could support future analytics workloads while reducing total platform costs.

Exponentia executed an end-to-end migration from the legacy Teradata environment to a Microsoft Fabric Lakehouse. The implementation included automated metadata extraction using custom scripts, complexity scoring, phased migration of more than 300 tables, and the use of a T-SQL Warehouse for structured analytics layers. The modernized platform also enabled downstream Power BI and Azure ML workloads.