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sales analysis project using PySpark provides valuable insights into customer behavior, sales trends, and product performance. These insights can inform strategic decision-making to enhance customer satisfaction, optimize marketing efforts, and improve overall business performance

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Sales-Analysis-using-PySpark-on-Databricks

Introduction

This project is designed to uncover valuable insights into sales trends, customer behavior, and product performance.

Datasets

The analysis makes use of two primary datasets:

  1. Sales Transaction Dataset:

    • Contains detailed information about each sales transaction.
    • Includes customer ID, product ID, quantity purchased, transaction date, and total amount spent.
  2. Product Information Dataset:

    • Includes product category, product description, and product price.

Analysis

The analysis is structured around key aspects of the business:

Customer Spending

  • Total Amount Spent by Customer: Analyzes the total amount spent by each customer to identify high-value customers.

  • Frequency of Customer Visiting Restaurant: Examines the frequency of customer visits to understand customer loyalty patterns.

Sales Trends

  • Total Amount Spent by Each Food Category: Categorizes sales based on food categories to identify popular and less popular items.

  • Total Amount of Sales in Each Month: Analyzes monthly sales trends to identify seasonal patterns and peak sales periods.

  • Yearly Sales: Investigates annual sales trends to assess year-over-year growth and identify growth opportunities.

Product Performance

  • How Many Times Each Product Purchased: Determines the popularity of each product based on purchase frequency.

Geographical Analysis

  • Total Sales By Each Country: Analyzes sales distribution across different countries to identify key markets.

Order Source Analysis

  • Total Sales by Order Source: Examines sales trends based on order sources (online, in-store, mobile app) to optimize marketing strategies.

Dashboard

Visualize the key insights obtained from the analysis questions on the Sales Analysis Dashboard.

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sales analysis project using PySpark provides valuable insights into customer behavior, sales trends, and product performance. These insights can inform strategic decision-making to enhance customer satisfaction, optimize marketing efforts, and improve overall business performance

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