📊 Sales Analysis

Analyze the company dataset and extract actionable insights.

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Table of Contents

• Overview
• Business Problem
• Dataset
• Tools & Technologies
• Research Questions & Key Findings
• Dashboard
• Output
• Author & Contact

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🧾 Overview

This project delivers a dynamic and interactive sales analysis designed to uncover key business insights, optimize performance, and support data-driven decision-making. Built with a focus on flexibility and clarity, the dashboard empowers users to explore sales data across multiple dimensions.

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❓ Business Problem

Business Questions Addressed

• Top/Bottom 5 Products
  Identify the highest and lowest performing products by:

  • 💰 Sales Revenue
  • 📈 Profit
  • 📦 Quantity Sold

• Sales Trends Over Time
  Analyze how sales evolve across:

  • 📅 Daily
  • 🗓️ Monthly
  • 📊 Quarterly
  • 📆 Annual intervals

• Sales vs Profit Relationship
  Visualize and quantify the correlation between sales and profit to assess margin efficiency.

• Period-over-Period Comparison
  Compare sales, profit, and quantity sold between any two user-selected time periods to detect growth, decline, or seasonal shifts.

• Discount Analysis
  Calculate the average discount offered across each discount category to evaluate promotional effectiveness.

• Order Volume
  Display the total number of orders to gauge transaction frequency and customer engagement.

• Order-Level Insights with Filters
  Explore detailed metrics for each order, including:

  • 💵 Sales
  • 📊 Profit
  • 🎁 Discount
  • 🧾 Net Sales
  • 🔍 All remaining fields
    Filterable by:
  • 🛍️ Product
  • 📆 Date
  • 🧑 Customer ID
  • 🎯 Promotion Category

• City-Level Sales Distribution
  Break down sales performance by city to identify geographic trends and regional opportunities.

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📂 Dataset

• Multiple CSV files located in the /data/ folder:
  • Dim_Customers.csv
  • Dim_Facts.csv
  • Dim_Product.csv
  • Dim_Promotion.csv

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🛠️ Tools & Technologies

• Power BI for interactive visualizations
• Power Query M for data transformation
• DAX for advanced calculations and dynamic filtering

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📌 Research Questions & Key Findings

• Top/Bottom Products: High-performing products align across sales and profit, while some low-profit items show high quantity sold—indicating pricing or cost issues.
• Sales Trends: Clear seasonality observed, with spikes during promotions and holidays.
• Sales vs Profit: Positive correlation overall, but some products show high sales with low margins.
• Period Comparison: Growth varies by category and region; useful for evaluating promotions and market shifts.
• Discounts: Higher discounts boost sales but don’t always improve profit.
• Order Volume: Peaks during campaigns and end-of-quarter periods.
• Filtered Insights: Filters reveal nuanced patterns across customer behavior and product performance.
• City Sales: Urban centers dominate revenue; regional targeting recommended.

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📊 Dashboard

Interactive Power BI dashboard showcasing all metrics and filters described above.

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🚀 Output

This dashboard equips stakeholders with a clear, customizable view of sales performance across products, time, geography, and promotions. It supports strategic planning, inventory optimization, and targeted marketing decisions.

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👤 Author & Contact

Tanay Srivastava
Data Analyst
📧 Email: tanaysrivastava562@gmail.com
🔗 LinkedIn

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