🔍 Project Overview
This project presents a comprehensive analysis of Reliance Smart's sales performance, customer behavior, and inventory management using a Power BI dashboard. The report leverages data transformation, modeling, and DAX functions to generate insights on key metrics like revenue, profit, and returns, comparing them to previous months for trend analysis.
The analysis is based on seven key tables:
- Stores: Data on store locations, sizes, and types.
- Calendars: Date-related information (day, month, year) to analyze sales trends.
- Customers: Customer demographics and purchasing behavior.
- Regions: Geographic locations and regions of stores.
- Transactions: Records of sales, including items sold, prices, and quantities.
- Returns: Tracks items returned by customers and reasons for returns.
- Products: Details on products sold, including categories, prices, and availability.
The dashboard focuses on the following KPIs, comparing each to the previous month:
- Revenue vs Previous Month: Tracks monthly revenue growth or decline.
- Profit vs Previous Month: Monitors profit trends on a month-over-month basis.
- Returns vs Previous Month: Analyzes the change in product return rates over time.
- DAX Functions for Calculations: Utilized to calculate revenue, profit, and return metrics.
- Data Cleaning & Transformation: Performed to ensure data accuracy and consistency before modeling.
- Data Standardization: Ensured uniform data structure for analysis.
- Data Modeling: Created relationships between tables (e.g., Transactions, Products, Customers) to support accurate reporting.
- Interactive Dashboard: Filters for exploring revenue, profit, and returns by store, product, and region.
- Revenue growth has shown a steady increase, with grocery and household items being the top-selling categories.
- Profit margins are highest in medium-sized stores located in Tier 2 cities, highlighting potential for expansion in these areas.
- Return rates for electronics continue to rise, suggesting a need to improve product quality or customer service in that category.
- Power BI: For dashboard creation, data modeling, and visualization.
- DAX Functions: For performing calculations and creating KPIs.
- Power Query: Used for data cleaning, transformation, and standardization.
- Download the Power BI Report: Link to the Power BI File
- Open Power BI: Load the file into Power BI Desktop.
- Interact with the Dashboard: Use slicers and filters to explore data by store, region, and product category.
Note: This analysis was conducted for educational purposes and does not reflect real-world financials.
For any questions or feedback, feel free to reach out via LinkedIn: Mayank Yadav