E-commerce Web Sales Dashboard

This project presents an in-depth data analysis of an E-commerce website sales report dashboard using Power BI. The data is sourced from CSV files and the process involves several steps: Data Preparation

The first step is data preparation. This involves formatting all the necessary data in CSV files that contain order details, product details, customer details, etc. These files are then cleaned and structured to contain all the relevant data needed for the dashboard. Importing Data into Power BI

Next, the data is imported into Power BI. This is done by clicking on "Get Data" in the Home tab, selecting "Text/CSV" from the dropdown menu, and navigating to where the CSV files are stored. This step is repeated for all the CSV files to be included in the dashboard. Data Modeling

After importing all the CSV files, relationships are created between different data tables in Power BI's relationship view. For instance, an 'Orders' table can be linked with a 'Customer Details' table via a common column (like 'customer_id'). Creating Calculated Fields

Depending on the requirements, calculated fields such as Total Sales, Average Order Value, etc., might need to be created. This is done using DAX (Data Analysis Expressions) in Power BI. Visualization

Visualizations are created using Power BI's drag-and-drop interface to create charts, graphs, maps, and other visuals. For an e-commerce dashboard, visuals showing total sales over time, top-selling products, customer demographics, etc., are included. Dashboard Design

Once all the visuals are created, they are arranged on the dashboard in an intuitive and easy-to-understand manner. Filters, slicers, and drill-through actions are added for more interactivity. The final product is a comprehensive and interactive E-commerce website sales report dashboard that provides valuable insights into the business's performance.