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.

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