Case Study 10. Marine Dealership, Multi-Location Data Warehouse
Industry: Marine Retail and Data Engineering. Timeline: 2024 to Present.
The Problem.
A marine dealership with multiple locations already ran its business on its numbers. Its team pulled sales, service, inventory, and customer reports out of the point-of-sale system by hand and assembled them location by location. The discipline was there; the infrastructure was not. Every report took hours to build, a view across locations meant stitching spreadsheets together, and the process depended on the people who knew where each number lived. As the business grew, the manual approach was not going to grow with it.
The Solution.
I am building the dealership a complete data warehouse that automates the reporting its team had been doing by hand and brings it all into one place. It draws from every part of the operation, customers, transactions, boat and unit sales, deals, service labor, and parts, and moves that raw system data through progressive layers of cleaning and structuring until it is reliable enough to base real decisions on. It is built on Microsoft Azure’s data platform, chosen so it can grow with the business and connect to whatever comes next.
Early in the work I found that free-form comment fields in the point-of-sale system held customer card numbers, a common side effect of older systems that let staff type anything into a notes field. I documented it and raised it right away, so the dealership could close the risk before it became a problem. I am also designing the layer that will feed this clean data into the dealership’s sales and customer systems.
The Outcome.
The dealership’s team is moving from assembling reports by hand to having its entire operation in one queryable place, with the reporting it already relied on now automated, structured, and spanning every location. The card data issue was caught and documented before production reporting began. The engagement is active and expanding, with the next phase connecting the warehouse into the dealership’s sales and customer platforms.
[To add, pending client approval: number of locations, data volume, and the specific decisions the warehouse has made possible. This case is written to be updated as the engagement progresses.]
For me this is a familiar pattern at a larger scale: taking data and operations that have never been connected to each other and turning them into a system a business can actually run on.