📊 Sales Analysis Power BI Dashboard

Welcome to the Sales Analysis Dashboard repository. This project showcases a dynamic Power BI dashboard built to provide in-depth insights into sales performance across multiple dimensions such as products, customers, regions, and financial metrics. The dashboard is designed to support strategic decision-making by providing a visually appealing and interactive platform for analyzing sales data.

---

🚀 Project Overview

This Sales Analysis Dashboard is built to help business stakeholders and data enthusiasts gain actionable insights into various aspects of sales. It consolidates data from different tables and enables multi-dimensional analysis. Users can interactively explore sales trends, identify high-performing products, understand customer demographics, and assess regional performance.

The goals of this dashboard are to:

1. Provide a clear, concise view of overall sales performance.
2. Offer detailed insights into customer and product-based trends.
3. Facilitate strategic planning by visualizing financial metrics and regional data.

---

📐 Data Model

The data model is central to this dashboard, combining multiple tables to support detailed analysis. Here's an overview of each table:

• fact_sales: Contains transactional data such as OrderDate, Profit, TotRevenue, TotOrders, and other essential sales metrics.
• Dim_calendar: A comprehensive date dimension table used for time-based analysis, with fields like Date, Month, Year, Weekday, and Quarter.
• Product_Categories: Holds information on product categories, linked to subcategories for detailed product analysis.
• Customers: Contains demographic details about customers, such as AnnualIncome, MaritalStatus, and EducationLevel.
• Returns: Stores return information for each product, enabling return rate analysis by product.
• Territories: Provides geographical data, linking sales transactions to regions and countries.

Below is the data model used in Power BI:

---

🖥️ Dashboard Sections & Visuals

The dashboard is organized into multiple sections, each designed to provide targeted insights. Here’s a breakdown of each page:

1. Home Page

• Purpose: Acts as a landing page, offering quick navigation options to each analytical section: Product, Customer, Product Details, Region, and Ranking.
• Key Visual: Icons for each section for intuitive navigation.
• 

2. Product Analysis

• Content: Analyzes sales performance by product category and subcategory.
• Visuals:
  • Sankey Diagram: Visualizes revenue flow by product category and subcategory.
  • Bar Chart: Year-over-year revenue comparison for top product categories.
• Insight: Identifies top-performing products, helping in strategic product planning.
• 

3. Customer Insights

• Content: Examines customer demographics and purchase patterns.
• Visuals:
  • Donut Chart: Shows customer distribution by Marital Status and Parenting Status.
  • Bar Chart: Sales by customer Occupation.
  • Stacked Bar Chart: Sales by product and gender.
• Insight: Provides a clear view of customer profiles, assisting in targeted marketing efforts.
• 

4. Geographical Analysis

• Content: Visualizes sales across different countries and income levels.
• Visuals:
  • Map: Interactive map highlighting total orders by country, segmented by income level.
  • Flag Icons: Country filters for an easy selection of regions.
• Insight: Reveals geographical sales distribution, identifying high-potential regions for expansion.
• 

5. Financial Performance

• Content: Tracks quarterly financial performance and revenue targets.
• Visuals:
  • Line Chart: Monthly revenue compared to target goals.
  • Bar Chart: Profit analysis by quarter.
  • Pie Chart: Cost breakdown by subcategory.
• Insight: Helps assess progress towards financial goals and analyze profitability across categories.

6. Product Ranking

• Content: Ranks top products by revenue and profit contribution.
• Visuals:
  • Table: Detailed breakdown of top products with revenue and profit metrics.
  • Bar Chart: Visualization of top N products based on total revenue.
• Insight: Identifies key revenue drivers and top-performing products for sales strategy. -

🛠️ How to Use the Dashboard

Setup Instructions

1. Prerequisites: Ensure Power BI Desktop is installed.
2. Download: Clone or download the .pbix file from this repository.
3. Open File: Open the .pbix file in Power BI Desktop.
4. Data Refresh: If connected to live data sources, refresh the data to ensure visuals are up-to-date.

Navigating the Dashboard

1. Home Page: Start at the Home Page to select a section for analysis.
2. Interactive Filters: Each page includes slicers and filters, such as Year, Product Category, and Subcategory, for focused analysis.
3. Drill-Downs: Click on visuals to explore underlying details and segment data further.
4. Tooltips: Hover over data points for additional metrics and insights.

---

🔍 Data Insights & Interpretation Guide

• Revenue Analysis: The Product Analysis page allows you to see which categories drive the highest revenue, helping identify profitable areas.
• Customer Segmentation: Use Customer Insights to determine which demographics contribute most to sales, informing targeted marketing strategies.
• Regional Performance: The Geographical Analysis highlights regions with high sales volumes, guiding regional sales strategies.
• Financial Health: The Financial Performance page offers a quick assessment of whether revenue targets are being met, with quarterly breakdowns for seasonality insights.
• Top Product Ranking: The Product Ranking page showcases the best performers, helping focus on products that maximize revenue.

---

📝 License

This project is licensed under the MIT License. Please see the LICENSE file for more information.

---