This project focuses on the development of an interactive dashboard to analyze retail performance for Real Mart. By processing datasets sourced from Kaggle, the project transforms complex retail data into clear, actionable business insights. The goal is to provide stakeholders with a comprehensive view of sales trends, profitability, and inventory health.
- Sales Performance Tracking: Visualizing revenue trends over time to identify seasonal peaks.
- Product Category Analysis: Deep dive into which product lines drive the most profit.
- Profit Margin Monitoring: Detailed breakdown of margins by region and category.
- Inventory Optimization: Helping business owners make data-driven decisions on stock levels and inventory tracking.
- Interactive Filters: Users can filter data by Date, Region, and Product Category for specific insights.
- Power BI Desktop: Used for creating the data model and interactive visualizations.
- Power Query: Utilized for data cleaning, ETL (Extract, Transform, Load) processes, and handling null values.
- DAX (Data Analysis Expressions): Implemented for complex calculations, KPIs, and Year-over-Year (YoY) growth metrics.
- Kaggle: The primary source for the retail dataset.
DATA ANALYTIC.png- Primary screenshot of the developed dashboard.Real Mart Data.pbix- The Power BI project file (contains the model and report).Dataset/- Folder containing the raw CSV/Excel files from Kaggle.
- Top Categories: Identified the top 3 product categories contributing to over 60% of total revenue.
- Profitability: Discovered that while certain items have high sales volume, their profit margins are lower due to high shipping costs.
- Seasonality: Sales trends indicate a significant spike in the final quarter, suggesting a need for increased inventory in Q4.
- Download the repository to your local machine.
- Ensure you have Power BI Desktop installed.
- Open the
.pbixfile to interact with the dashboard.