The workflow before
Robbins Brothers ran reporting off DecisionCast, an on-premise warehouse near end of life, with financial data in Oracle EBS and customer data in Salesforce. Daily reports were Excel workbooks that staff rebuilt by hand from extracts. The monthly close took more than 10 days, sales reports took days, and store managers could not compare locations or see inventory across the 15 showrooms.
What we built
Across three engagements (strategy, core build, then expansion) we replaced DecisionCast with a cloud warehouse on Azure and Snowflake. Azure Data Factory pulls Oracle EBS, Salesforce and headcount data into Azure Data Lake Storage, with Apache Airflow handling scheduling, dependencies and retries.
In Snowflake we modeled sales, inventory, customer, finance, headcount and product data marts on a shared semantic layer, so every report uses the same definitions. Power BI sits on top with executive dashboards, store performance dashboards and self-service reporting for business users.
The phased approach moved the highest-value sources first, so finance and store teams were working from live dashboards before the later sources were added.
Before and after
| Measure | Before | After |
|---|---|---|
| Monthly financial close | 10+ days | 5 days |
| Sales report turnaround | Days | Minutes |
| Inventory view across showrooms | Weekly, manual | On demand |
| New dashboard build | Weeks | Days |
What's next
Sales, inventory and customer data now live in one governed Snowflake model. That is the foundation for L2 work: an analytics assistant for store and finance teams, and demand forecasting on the 40% of bridal business that is special order.
