Super Store Sales Analysis Dashboard using Power BI

This project involves the analysis of two years' worth of sales data from a super store. The data, initially in Excel format, contained information such as Order ID, Order Date, Ship Date, Ship Mode, Customer ID, Customer Name, Segment, Country, City, State, Region, Product ID, Category, Sub-Category, Product Name, Sales, Quantity, Profit, Returns, and Payment Mode.

The initial step involved data cleaning, addressing null values, and removing extraneous columns to ensure a clean dataset. Subsequently, a comprehensive dashboard was created using Power BI to provide a visual representation of the sales data.

The dashboard includes key performance indicators represented as cards, displaying critical metrics such as total sales, total profit, returned products and total quantity sold along with maps and charts for deeper insights. Specifically, a map chart was utilized to identify regions generating the highest profits, providing geographical context to the data.

Additionally, two pie charts were incorporated to visualize the distribution of payment modes and sales by segment, offering a clear understanding of payment trends and customer segmentation. Two bar charts were employed to illustrate sales by city and category, as well as profit and sales figures, allowing for a comprehensive view of sales performance across different dimensions.

A line chart was included to track sales and profit trends over the course of each month, offering insights into seasonal variations and performance patterns. To enhance interactivity, slicers were implemented to facilitate easy data filtering by month and year.

Furthermore, tooltips were integrated into the cards to efficiently compare metrics across the two years, providing a dynamic and informative user experience. This Power BI dashboard now serves as a powerful tool for stakeholders to quickly and intuitively understand the sales performance of the superstore over the specified period.