A comprehensive Power BI project that analyzes Walmart store sales across time, locations, departments, and external factors like holidays and weather. This dashboard provides actionable, business-ready insights to optimize operations and sales strategies.
- π Dashboard Pages & Insights
- π¦ Dataset Information
- π Tools Used
- π Dashboard PDF Preview
- π How to Use
- π§ Author
- βοΈ Give a Star
- Line Chart: Weekly Sales Trend with optional rolling average.
- Donut Chart: Sales Contribution by Year.
- Bar Chart: Top 10 Performing Stores.
- Stacked Column Chart: Sales by Store Type.
π‘ Key Insights:
β’ Track sales fluctuations over time.
β’ Identify high-performing stores.
β’ Analyze performance by store type.
- Matrix Table: Weekly Sales by Store and Department.
- Bar Chart: Top 10 Departments by Total Sales.
- Map Visual: Store locations with sales volume indicators.
π‘ Key Features:
β’ Conditional formatting to highlight performers.
β’ Drill-through navigation to department-level data.
β’ Geospatial sales performance insights.
- Line Chart: Sales Trends with Holiday markers.
- Scatter Plot: Weekly Sales vs. Temperature.
- Line Chart: Weekly Sales vs. Fuel Price.
- Bar Chart: Holiday vs. Non-Holiday Week Sales.
π‘ Business Impact:
β’ Understand sales behavior during holidays.
β’ Identify influence of weather and fuel prices.
β’ Enhance planning with seasonal trends.
Feature | Description |
---|---|
Rows | 421,570 |
Columns | 18 |
Format | CSV |
Sample Columns | Store, Dept, Date, Weekly_Sales, CPI, Unemployment, Fuel_Price, etc. |
Source | Walmart Sales Dataset (public) |
Tool | Purpose |
---|---|
Power BI | Data modeling, DAX, dashboard visuals |
Python (optional) | Data preprocessing (pandas) |
Excel/CSV | Raw data handling and import |
π View the full interactive dashboard design here:
π Walmart Sales Analytics Dashboard (PDF)
- Clone the repository or download the
.pbix
files. - Open any
.pbix
file in Power BI Desktop. - Interact with visuals and slicers.
- Modify or extend visuals as needed for your analysis.
Priyanka Malavade
π Aspiring Data Analyst | Turning data into decisions
π§ [email protected]
π LinkedIn
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