Overview

I designed and deployed a cloud-native Business Intelligence suite to provide real-time visibility into multi-channel eCommerce performance. By consolidating data from Takealot, Amazon, and MintSoft into a centralized Azure SQL backbone, I created a "Single Version of Truth" for inventory valuation, sales velocity, and cross-platform financial performance analysis.

Technical Deep Dive

Data Architecture & Cloud Integration

• The Technology: Engineered a robust ETL pipeline that fetches data from Azure SQL and CSV/Excel files hosted in Azure Blob Storage. This architecture ensures the model is "Cloud Native," allowing for scheduled refreshes independent of local hardware or user sessions.
• The Impact: Eliminated the "Siloed Data" problem. The dashboard provides a unified view of the business, where warehouse stock levels and marketplace sales are automatically synced and reconciled without manual intervention.

Advanced DAX & Semi-Additive Modeling

• The Technology: Implemented sophisticated DAX measures to handle semi-additive inventory snapshots. Unlike sales, inventory cannot be summed over time; it requires "Latest Snapshot" logic.
  • Example: I authored Latest Visible Inventory Date and Inventory Value (Latest) measures that use CALCULATE, VALUES, and FILTER to ensure that when a user selects a month, the report displays the stock value as it existed on the final day of that period, not a sum of the whole month.
• The Impact: We can now accurately track the total capital tied up in stock across all fulfillment centers at any specific point in history.

Cross-Fact Intelligence (The "Has Data" Logic)

• The Technology: Developed complex "Context-Aware" measures (like Has Data (All Facts)) to manage the relationship between Sales, Inventory, and Warehouse tables. By calculating dynamic Min/Max date ranges across three disparate fact tables, the model automatically adjusts its visual range to show only relevant data.
• The Impact: Enhanced User Experience. The dashboard "self-cleans" by hiding empty time periods, ensuring that analysts only focus on periods where active trading or inventory movement occurred.

Business Insights & UI/UX

• Star Schema Optimization: The model is built on a high-performance Star Schema, separating Dimensions (Products, Calendar) from Facts (Sales, Inventory) to ensure sub-second report responsiveness.
• Financial Reconciliation: Automated the calculation of Marketplace Inventory Value by using RELATED functions to pull cost-price data from the product master, providing an instant view of gross margin potential.
• Data Storytelling: The report canvas utilizes interactive slicers and drill-throughs, allowing a user to see the "Big Picture" (Total Sales Value) before diving into specific SKU-level performance or DC-specific stock issues.

Cloud Native Data Access Design & Implementation