This repository highlights my ability to perform Data Analysis and Dashboard Creation using Power BI. It contains a dataset based on sales performance, customer, and product profitability, cleaned and transformed for analysis. The project focuses on showcasing my skills in data cleaning, data visualization, and interactive dashboards.
Here are a few screenshots of the Power BI dashboards:
The original dataset contains the following columns:
- OrderNumber
- Sales Channel
- WarehouseCode
- ProcuredDate
- OrderDate
- ShipDate
- DeliveryDate
- CurrencyCode
- SalesTeamID
- CustomerID
- StoreID
- ProductID
- Order Quantity
- Discount Applied
- Unit Cost
- Unit Price
After cleaning the data (standardizing date formats, etc.), I created additional calculated columns to enhance the analysis:
- R-Procured Date
- R-Order Date
- R-Ship Date
- R-Delivery Date
- Total Sales
- Total Cost
- Profit
- Profit without Discount
- Delivery Performance
This project includes two dashboards that visually present the results:
-
Sales Performance Dashboard
- Focus: Sales team performance, quarterly order growth, and overall sales.
- Visuals:
- Pie Chart: Sales team performance breakdown.
- Stacked Area Chart: Sales trends over time.
- Slicers: Filter data by Date and Sales Channel.
- Bar Charts & Cards: Display key metrics such as quarterly sales and total sales.
-
Customer & Product Analysis Dashboard
- Focus: Product profitability and customer value analysis.
- Visuals:
- Tree Map: Product profitability analysis.
- Clustered Bar Chart: Profit and cost comparison across warehouses.
- Warehouse Analysis: Profit contribution by warehouse and customer value assessment.
In addition to the dashboards, I have demonstrated my proficiency with key Excel functions for data analysis:
- XLOOKUP
- COUNTIFS
- SUMIFS
- IFS
- Conditional Formatting for visual data highlighting.
The Power BI dashboards are designed to be highly interactive:
- Slicers: Allow filtering by time range, departments, sales channels, etc.
- Dynamic Charts: Adjust based on slicer selections to give users an intuitive exploration experience.
- Charts Used: Pie charts, stacked bar charts, line graphs, tree maps, clustered bar charts, and more.