Requirement Document for Amazon Sales Power BI Report

1. Introduction

This document outlines the requirements for the Power BI report analyzing sales data for an e-commerce platform. The report provides insights into sales performance across different product categories, locations, order statuses, and time periods.

2. Objectives

• To analyze sales trends across different regions.
• To track product performance.
• To monitor order statuses and returns.
• To evaluate sales by category and state.
• To provide a comprehensive sales summary.

3. Data Sources

The Power BI report utilizes sales transaction data, including:

• Order details (Order ID, Status, Date, etc.)
• Product details (Category, Name, Quantity Sold, etc.)
• Shipping details (City, State, Status, etc.)
• Financial details (Total Sale Amount, Revenue by Product, etc.)

4. Report Components

4.1 Sales Overview

• Total Sales Amount: $96.79M
• Total Orders: 126K
• Number of Sellers: 35

4.2 Sales Breakdown by Status

• Shipped: $62M
• Cancelled: $9M
• Returned/Rejected: $3M
• Pending: $1M

4.3 Sales by City & State

• Top Performing Cities:
  • Bengaluru: $8.8M
  • Hyderabad: $6.8M
  • Mumbai: $5.4M
  • New Delhi: $4.7M
• Top Performing States:
  • Maharashtra: $17M
  • Karnataka: $13M
  • Tamil Nadu: $9M

4.4 Sales by Category

• Top-Selling Categories:
  • Ethnic Dress: 47K units
  • Western Dress: 47K units
  • Saree: 1K units

4.5 Sales by Product

• Top-Selling Products:
  • Max Boy’s Regular Shirt: 322 units
  • BIBA Women’s Straight Dress: 294 units

4.6 Sales Over Time

• Sales trend from April 2022 to June 2022 showing revenue fluctuations.

5. Functional Requirements

5.1 Data Filters & Drilldowns

• Filter by product category
• Filter by city/state
• Filter by sales status
• Filter by date range

5.2 Visualizations

• Bar Charts: Sales by city, state, and product
• Line Charts: Sales trend over time
• Pie Charts: Order status breakdown

6. Non-Functional Requirements

• The report should be accessible via Power BI Desktop.
• It should support real-time data updates.
• The report should be optimized for quick loading and interaction.

7. Assumptions

• Sales data is updated in real-time.
• All product categories are accurately classified.
• Order statuses are correctly recorded.

8. Project Completion Method

8.1 SQL Queries

• Data extraction from the database using SQL queries.
• Example query to fetch sales data:

SELECT OrderID, ProductName, Category, SaleAmount, OrderStatus, OrderDate, City, State FROM SalesData WHERE OrderDate BETWEEN '2022-04-01' AND '2022-06-30';

• Data transformation using SQL joins and aggregations.

8.2 Power Query

• Importing and transforming data from multiple sources.
• Cleaning and shaping data (removing duplicates, handling missing values).
• Merging datasets to create a comprehensive sales dataset.

8.3 DAX (Data Analysis Expressions)

• Creating calculated columns and measures for analysis.
• Example DAX formulas:

TotalSales = SUM(SalesData[SaleAmount])SalesByCategory = CALCULATE(SUM(SalesData[SaleAmount]), SalesData[Category] = "Ethnic Dress")

• Time intelligence functions for trend analysis.

9. Conclusion

This Power BI report is designed to provide actionable insights into e-commerce sales performance, helping stakeholders make informed business decisions.

1. SalesData.csv – Contains order details, product info, and sales transactions.
2. ProductDetails.csv – Includes product categories, names, and sales quantities.
3. ShippingData.csv – Contains order statuses, shipping details, and delivery locations.