This project demonstrates a comprehensive sales analysis solution using a combination of MySQL for data processing and Power BI for interactive data visualization. It reflects real-world practices in data modeling, business intelligence, and dashboard design, suitable for decision-makers, analysts, and business users.
The goal of this project is to analyze and visualize retail sales data to uncover business insights and performance trends. A normalized relational database schema is created in MySQL, and SQL queries are used to build a consolidated reporting table. This data is then visualized in Power BI using a clean, well-designed interactive dashboard.
The dashboard provides metrics and visuals to answer key business questions such as:
- Who are the top customers by sales?
- Which products are the most sold?
- What is the profit classification across categories?
- Which customer segments are most profitable?
- Are there customers who have not placed any orders?
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Sales_Analysis_Dashboard.pbix
The main Power BI Desktop file containing the full interactive dashboard, KPIs, filters, and visuals. -
sales_analysis_query.sql
The SQL script used to create the normalized data schema, join the tables into a unifiedsales_table, and generate business insights. -
README.md
Project documentation explaining the workflow, features, and how to use the files.
- MySQL: Used for creating normalized tables, managing relational data, and writing analytical queries.
- Power BI Desktop: Used to develop a responsive, interactive dashboard with dynamic visuals and KPI cards.
- SQL: Used for data extraction, transformation, joining, and aggregating business metrics.
- DAX: Utilized within Power BI for calculated columns and measures where required.
The database is modeled using a normalized structure with the following tables:
customers: Contains customer ID, name, segment, and region.orders: Contains order ID, order and shipping dates, customer ID, and region.order_details: Contains customer ID, product ID, quantity, sales, and profit.products: Contains product ID, category, sub-category, and product name.
All tables are joined using appropriate keys to create a single, consolidated reporting table called sales_table. This table serves as the primary source for Power BI visuals.
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Profit Classification
Products are categorized as "Profit", "Loss", or "No Profit No Loss" based on their profitability using conditional logic. -
Top Customers by Sales
Identifies the top five customers based on the total sales amount. -
Customers with the Most Orders
Returns the customer who placed the maximum number of orders. -
Inactive Customers
Lists customers who have never placed an order, which may be useful for marketing or retention strategies. -
Average Profit by Segment
Calculates the average profit across different customer segments. -
Top Products by Units Sold
Identifies the five most sold products based on quantity.
All queries are written in clean, readable SQL and can be reused or adapted for other datasets.
The Power BI report includes the following visuals and functionality:
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KPI Cards:
- Total Sales
- Total Profit
- Total Orders
- Average Order Value
- Profit Margin
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Visual Charts:
- Donut chart displaying profit classification
- Bar charts showing top customers and product sales
- Line chart for monthly sales trends
- Data table for regional sales by category
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Filters and Segments:
- Slicers for customer segment, region, and product category
- Responsive visuals that update dynamically with user input
The layout follows a clean, user-friendly design with clear headings, minimal color clutter, and consistent formatting.
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Load SQL Data
Execute the script insales_analysis_query.sqlon your MySQL server. It will create the necessary tables and populate the unified reporting table (sales_table). -
Open Power BI Report
The Power BI report includes:
- Key metrics: total sales, profit, average order value, etc.
- Interactive filters for region, customer segment, and category
- Visualizations including bar charts, donut charts, and trend lines
You can view the dashboard layout in the image below and download the .pbix file to explore it interactively in Power BI Desktop.
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Connect Data Source
Update the data source connection settings in Power BI to point to your local or hosted MySQL database. Use the appropriate credentials. -
Refresh the Report
Click "Refresh" in Power BI to load the data and view the updated dashboard.
Karthika Karthika
Email: karthikab214@gmail.com
This project is open for educational and professional showcase purposes. If you use or modify this work, please credit the original author.
This end-to-end project demonstrates essential skills for a data analyst or BI developer, including:
- Data modeling and ETL in SQL
- KPI development and business insight extraction
- Interactive dashboard creation in Power BI
It provides a complete view of the analytics process, from raw data to insight-driven storytelling.