This project presents an end-to-end Retail Business Intelligence Dashboard built using Power BI to analyze sales performance, inventory health, supplier reliability, and store profitability.
The dashboard integrates sales analytics, inventory risk monitoring, supplier supply analysis, and profitability insights to simulate a real-world retail analytics environment focused on operational efficiency and supply chain intelligence.
The objective of this project was to:
- Design a clean star-schema data model
- Implement advanced DAX measures
- Build executive-ready KPI dashboards
- Monitor inventory health and stockout risks
- Analyze supplier contribution and supply chain reliability
- Deliver actionable business insights for retail operations
- Measure overall retail sales and profitability performance.
- Identify high-performing stores and product categories.
- Monitor inventory levels and detect stockout risks.
- Analyze supplier contribution to inventory supply.
- Track supply vs demand balance across the business.
- Provide insights to improve retail operations and inventory planning.
The dataset consists of the following tables:
| Table | Description |
|---|---|
fact_sales |
Sales transactions including revenue, cost and quantity sold |
fact_inventory |
Current inventory stock levels |
fact_inventory_movements |
Inventory inflow and outflow movements |
dim_products |
Product catalog with categories and supplier information |
dim_stores |
Store location, region and store attributes |
dim_suppliers |
Supplier information and supply relationships |
dim_date |
Calendar table used for time intelligence |
MyMeasures |
Dedicated table to store all DAX measures |
The dataset simulates a real-world retail data warehouse structure.
The model follows a star schema structure:
fact_salesacts as the primary sales performance fact tablefact_inventorytracks inventory stock levelsfact_inventory_movementstracks inventory inflow and outflowdim_productsconnects products with categories and suppliersdim_storesenables store-level performance analysisdim_suppliersenables supplier contribution analysisdim_datesupports time intelligence calculations
Relationships are built using product_id, store_id, supplier_id and date keys with one-to-many cardinality.
This structure ensures proper filter propagation and accurate KPI calculations.
- Total Revenue
- Total Profit
- Profit Margin (%)
- Total Units Sold
- Sales Last Year
- Year-on-Year Growth (%)
- Inventory Health Score
- SKU Critical Risk Count
- Inventory vs Reorder Point
- Inventory Risk by Category
- Stockout Risk Indicator
- Stock In
- Stock Out
- Net Inventory Flow
- Supplier Inventory Contribution
- Supplier Stockout Risk Exposure
- Store Level Profit
- Category Profit Contribution
- High Margin Product Categories
- Profit Distribution by Region
All measures were implemented using proper filter context handling to ensure KPI accuracy across all dashboard filters.
- Total Revenue
- Total Profit
- Profit Margin (%)
- Total Units Sold
- Top Performing Store
- Sales & Profit Trend
- Sales Distribution by Region
Purpose: Provide a high-level executive overview of business performance, including revenue growth, profitability trends, and regional sales distribution.
- Inventory Health KPI
- Year-on-Year Growth (%)
- Category Performance Analysis
- Sales Performance by State (Map View)
- Inventory Risk by Category
Purpose: Analyze sales trends and category-level performance while monitoring inventory health.
- Inventory vs Reorder Point Analysis (Scatter Plot)
- Inventory Risk Trend
- Stockout Risk by Product Category
- Supplier Stockout Risk Contribution
- Top 15 Critical SKU Risk Table
Purpose: Detect inventory shortages, high-risk SKUs, and supplier-related stockout risks to support proactive inventory management.
- Top 10 Suppliers by Inventory Contribution
- Top Product Categories by Supplier Deliveries
- Inventory Flow Trend (Supply vs Demand)
- Net Inventory Flow KPI
Purpose: Evaluate supply chain reliability and supply-demand balance across the business.
- High Margin Product Categories
- Top 10 Stores by Profit
- Profit Contribution by Category
- Profit Distribution by State
Purpose: Identify profit drivers across stores and product categories to support better merchandising and pricing strategies.
To provide a complete 360° view of retail operations by combining:
- Sales Performance Analytics
- Inventory Risk Monitoring
- Supply Chain Contribution Analysis
- Store Profitability Insights
This enables businesses to balance revenue growth with operational efficiency and supply chain stability.
- Collapsible slicer panel for clean dashboard layout
- Interactive filtering across multiple pages
- Donut-based KPI progress visuals
- Map-based regional sales analysis
- Custom
MyMeasurestable for clean DAX management - Consistent KPI color themes for performance indicators
The dashboard balances analytical depth with professional presentation design.
- Sales performance varies significantly across regions and stores.
- Certain product categories show higher inventory risk compared to others.
- Supplier contribution analysis highlights inventory dependency patterns.
- Profit margins vary across categories indicating potential pricing opportunities.
- Net Inventory Flow helps monitor whether supply is exceeding demand or vice versa.
- Monitor high-risk SKUs and adjust reorder strategies.
- Improve supplier diversification to reduce stockout dependency.
- Focus on high-margin product categories to maximize profitability.
- Analyze underperforming stores for operational improvements.
- Align supplier deliveries with demand trends to prevent overstock or shortages.
- Power BI
- Data Modeling (Star Schema Logic)
- Advanced DAX Measures
- Power Query (Data Cleaning & Transformation)
- Retail & Supply Chain Analytics Techniques
- Business Intelligence Visualization Design
This project demonstrates:
- End-to-end BI dashboard development
- Strong data modeling fundamentals
- Advanced DAX implementation
- Retail and supply chain analytics
- Inventory risk monitoring techniques
- Business storytelling through dashboards
Suitable for roles in:
- Data Analyst
- Business Intelligence Analyst
- Retail Analytics
- Supply Chain Analytics
It reflects the ability to transform operational retail data into actionable business insights.
Note: For any questions or collaboration opportunities, feel free to reach out!