🍫 Sales Performance Analysis – Power BI Project

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1. Project Objective

This project analyzes multi-year transactional sales data (2021–2024) to evaluate revenue growth, profitability trends, product concentration, geographic performance, and seasonal behavior.

The objective is to transform over 10,000 sales transactions into structured commercial intelligence through a multi-page Power BI analytical report.

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2. Dataset Overview

Data Volume

• ~10,000 sales transactions
• 15 products
• 4 regions
• Time range: 2021–2024

Data Model

• Fact Table: Candy_Sales
• Dimension Tables: Candy_Products, Candy_Factories, Calendar

A dedicated Calendar table enables accurate Year-over-Year (YoY%) calculations and seasonal comparisons.

The report follows a structured star schema design, ensuring scalable filtering, clean relationships, and optimized performance.

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3. Dashboard Structure & Key Insights

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📊 Sales Performance Overview

Provides a high-level summary of revenue, cost, orders, division mix, regional performance, and shipping distribution.

Key Insights

• 2024 revenue reached ~47K with stable ~25% YoY growth.
• Profit growth accelerated from 23% (2023) to 28% (2024).
• Profit margin remained stable at ~5%, indicating scalable growth.
• Pacific and Atlantic regions are the most profitable.
• California, New York, and Texas generate ~40% of total sales.

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🍫 Product Analysis

Analyzes product-level contribution, margin behavior, and revenue concentration.

Key Insights

• Chocolate division generates over 90% of total revenue.
• 6 products (Wonka Bar flavors) account for 93.3% of total sales.
• Nutty Crunch has the highest margin (5.5%).
• Triple Dazzle Caramel has the lowest margin (4.6%).
• “Other” category grew ~40% YoY despite low overall share.

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🌎 Customer & Regional Segmentation

Examines geographic revenue distribution across regions, states, and cities.

Key Insights

• Revenue is heavily concentrated in metropolitan areas.
• San Francisco, Los Angeles, Houston, and New York City drive the highest purchasing volume.
• Idaho, Montana, and New Brunswick show the weakest sales performance.

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📈 Year-over-Year Performance & Seasonality

Evaluates growth sustainability and seasonal revenue patterns.

Key Insights

• Q4 contributes ~35% of total annual sales.
• November and December are peak revenue months.
• Q1 contributes only ~12.5% of annual sales.
• Sales growth remained consistent at ~25% in 2023 and 2024.

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🧩 Data Model – Star Schema

The report is built using a structured star schema design to ensure scalable filtering and accurate time intelligence calculations.

• Fact table: Candy_Sales
• Dimension tables: Candy_Products, Candy_Factories, Calendar

5. Technical Implementation

This project demonstrates:

• Star schema data modeling
• Dedicated Calendar table for time intelligence
• Advanced DAX calculations including:
  • Sales YoY %
  • Profit YoY %
  • Cost YoY %
  • Sales % of Total
  • Profit Margin %
  • Monthly vs Last Year comparison
• Context manipulation using CALCULATE, ALL, and filter context adjustments
• Multi-page analytical storytelling
• Geographic visualization using state and city-level mapping

Tools Used

• Power BI Desktop
• DAX
• Power Query

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Business Relevance

This analysis enables:

• Identification of revenue concentration risk
• Evaluation of growth sustainability
• Detection of high-performing regions and cities
• Assessment of product margin stability
• Recognition of emerging growth segments

The dashboard transforms transactional sales data into structured, decision-oriented commercial intelligence.