Created an interactive dashboard to track and analyze online sales data. The dashboard allows users to drill down into worksheets, customize views using filters and slicers, and leverage various visualization types to gain insights.
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Advanced Drill-Down and Customization: Utilized complex parameters to enable detailed drill-downs in worksheets, with extensive customization through filters and slicers.
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Data Manipulation: Loaded and manipulated data from CSV files, Established connections and joins between new tables, performed calculations to manipulate data,and created user-driven parameters to enhance visualizations.
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Custom Visualizations : Implemented a variety of customized visualizations, including:
- Bar Chart
- Pie Chart
- Donut Chart
- Clustered Bar Chart
- Scatter Chart
- Line Chart
- Area Chart
- Map
- Slicers
The dashboard tracks the following KPIs to provide insights into the performance of the ecommerce business:
- Total Sales (Sum of Amount): The total revenue generated from sales within a specific period.
- Sum of Quantity: The total number of items sold within a specific period.
- Sum of Profit: The total profit generated from sales.
- Average Order Value (AOV): The average amount spent per order, calculated as Total Sales divided by Number of Orders.
- Profit/Loss by Month: The profit or loss for each month, helping track monthly financial performance.
- Profit by Sub-Category: The total profit generated by each sub-category of products, providing insights into which sub-categories are most profitable.
- Data Source: CSV Files
- Data Visualization: Power BI
To set up the Madhav Ecommerce Sales Dashboard using Power BI and CSV files, follow these steps:
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Prepare the CSV Files:
- Ensure all your CSV files are in a single folder and are correctly formatted.
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Download and Install Power BI Desktop:
- Download Power BI Desktop from the official website.
- Follow the installation instructions to install Power BI Desktop on your machine.
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Load the CSV Files into Power BI:
- Open Power BI Desktop.
- Click on Get Data and select Text/CSV.
- Browse to the location of your CSV files and load them into Power BI.
- Repeat this step for each CSV file you want to include in the dashboard.
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Transform and Model the Data:
- Use the Power Query Editor to clean and transform the data as needed.
- Create relationships between tables if necessary.
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Create Visualizations:
- Use Power BI's visualization tools to create various charts, maps, and slicers.
- Customize the visuals to fit your analysis needs.
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Save and Publish the Dashboard:
- Save your Power BI file (.pbix).
- If desired, publish the dashboard to the Power BI Service to share it online.
- Open the Power BI Desktop file (.pbix) to view and interact with the dashboard.
- Use the slicers and filters to customize the view and drill down into specific data points.
If you have any questions or suggestions, feel free to reach out to us at shraddhalokhande25@gmail.com.