Transforming Data Management: A Retail Chain’s Success with Microsoft Fabric

About the client

Beginning with a single fuel station, this customer grew into a network of convenience stores, car washes, and food offerings. Renowned for its innovation, they are among the early adopters of self-service gas stations and pay-at-the-pump technology. The company has grown by expanding its food offerings, modernizing stores, and integrating advanced technologies across operations.


Client challenges

The customer faced several critical challenges in managing and utilizing their data. The lack of a central data repository and limited AI/ML capabilities impacted their ability to predict customer purchase behavior and forecast revenue. They also did not have real-time data integration or executive dashboards, which affected decision-making. The business relied heavily on manual reporting for ad hoc business needs.

Solution

We conducted a comprehensive Fabric Discovery and Readiness Assessment with the customer using our structured three-step approach. Through in-depth interviews and discovery sessions, we assessed and identified the key challenges. Leveraging these insights, we delivered a tailored roadmap with a phased implementation strategy to ensure data platform modernization with Microsoft Fabric. Our implementation helped minimize disruption, maximize ROI and resolve the customer’s data challenges.

  • Advanced Data Integration with Dataflow Gen 2 and Pipeline for seamless data integration from various sources.
  • Centralized Data Storage with OneLake to unify data storage, organized into a Medallion structure (Bronze – Raw, Silver – Curated, Gold – Aggregated).
  • Enhanced Reporting and Dashboards with Power BI reports and smart dashboards for better business insights.
  • Future-Ready Data Platform that is scalable, supports AI/ML activities, and facilitates real-time insights.
  • Optimized existing Power BI reports by repointing to Lakehouse data sources.
Results at a glance
20% reduction in time spent on operational reporting due to streamlined data processes optimizes costs. Enhanced forecasting and predictive insights through AI/ML models on customer behavior. Improved decision-making capabilities with consolidated executive dashboards and self-service reporting.
Benefits
  • Simplified Cost Management: The all-in-one pricing model helped streamline cost management and enabled the company to predict Fabric capacity consumption and costs.
  • Improved Data Performance: Significant performance improvements across various data workloads, enhancing operational efficiency.
  • Advanced Predictive Insights: Enabled AI/ML capabilities to analyze customer purchasing trends, leading to better business forecasting and increased sales and revenue.
  • Enhanced Self-Service Reporting: Empowering business users with easy data access through discoverable data models (Semantic Models).
  • Consolidated Executive Dashboards: Supporting strategic decision-making with a view of operational metrics.
  • Operational Efficiency: Achieved approximately 20% time savings in manual reporting processes, allowing the team to focus on higher-value tasks.
Technology

Microsoft Fabric, Power BI, SQL Server and Google BigQuery