#Project Overview This project focuses on analyzing sales data to uncover trends, patterns, and key insights that drive business decisions. Using Power BI, the project transforms raw sales data into interactive dashboards and reports, enabling stakeholders to monitor performance, identify opportunities, and optimize strategies.
Created a star schema with fact and dimension tables (e.g., Sales, Products, Customers, Dates).
Established relationships between tables to ensure accurate and efficient analysis.
Used DAX (Data Analysis Expressions) to create calculated columns and measures (e.g., YTD Sales, Profit Margins).
Sales Overview Dashboard:
Total Revenue, Profit, Quantity Sold, and Average Order Value (AOV).
Trend analysis with time-series charts (monthly, quarterly, yearly).
Product Performance Dashboard:
Top-selling products and categories by revenue/profit.
Product-level insights (e.g., regional sales, seasonality).
Customer Insights Dashboard:
Customer segmentation (new vs. returning, high-value customers).
Geographic analysis (sales by region, country, or city).
Sales Transactions: Order details, dates, quantities, and revenue.
Product Data: Categories, prices, and costs.
Customer Data: Demographics, regions, and purchase history.
Date Table: Custom calendar for time intelligence.
Power BI Desktop: For data modeling, visualization, and report creation.
Power Query: For data cleaning, transformation, and integration.
DAX: For advanced calculations and metrics.
Excel/CSV/SQL: Data sources integrated into Power BI.
Enabled data-driven decision-making with real-time dashboards.
Improved sales visibility and performance tracking.
Reduced manual reporting efforts by automating insights.
Power BI Report (.pbix): Interactive dashboards and visualizations.
Sample Dataset (.csv): Cleaned and processed sales data.
Screenshots: Preview of key dashboards and insights.