This project demonstrates an end-to-end Sales Analytics solution using Microsoft SQL Server and Microsoft Power BI. The objective was to transform raw data from a Data Warehouse into meaningful business insights through data extraction, transformation, modeling, and interactive dashboard development.
The project simulates a real-world Business Intelligence workflow, covering the complete analytics lifecycle from SQL-based data preparation to Power BI dashboard creation for strategic decision-making.
Organizations generate large volumes of transactional data every day. However, without proper analysis, valuable business insights remain hidden.
The objective of this project is to transform raw sales data into an interactive Business Intelligence solution that enables stakeholders to monitor sales performance, analyze customer behavior, evaluate product performance, and support data-driven business decisions.
- Extract and prepare data from SQL Server Data Warehouse.
- Clean and transform data using T-SQL.
- Design a scalable star schema data model.
- Develop an interactive Power BI dashboard.
- Analyze sales performance across customers, products, regions, and time.
- Deliver actionable business insights through data visualization.
- Microsoft SQL Server
- SQL Server Management Studio (SSMS)
- T-SQL
- Microsoft Power BI
- Power Query
- Data Modeling
- DAX
- SELECT Statements
- WHERE & ORDER BY
- GROUP BY & HAVING
- INNER JOIN
- LEFT JOIN
- CASE Statements
- Common Table Expressions (CTEs)
- Data Cleaning
- Data Transformation
- Column Formatting
- Conditional Logic
- Power Query
- Data Modeling
- Star Schema
- Relationships
- DAX Measures
- Interactive Dashboard
- KPI Cards
- Slicers
- Drill-Down Analysis
- Custom Visualizations
- Business Requirement Analysis
- Data Warehouse Restoration
- Data Exploration
- Data Cleaning using T-SQL
- Data Transformation
- Star Schema Data Modeling
- Power BI Data Import
- DAX Measure Creation
- Interactive Dashboard Development
- Business Insight Generation
- Business Recommendations
The dashboard provides interactive insights into:
- Sales Performance
- Revenue Analysis
- Budget vs Actual Performance
- Customer Analysis
- Product Performance
- Geographic Sales Distribution
- Top Customers
- Top Products
- Sales Trends
- KPI Summary
- Identified top-performing products and customer segments contributing to overall revenue.
- Analyzed sales trends across different time periods to support forecasting and strategic planning.
- Compared actual sales against budget to evaluate business performance.
- Identified regional sales patterns to support location-based business decisions.
- Enabled interactive reporting for stakeholders through dynamic filtering and drill-down capabilities.
Based on the analysis, the following recommendations are proposed:
- Increase investment in high-performing products and profitable customer segments.
- Optimize inventory planning using historical sales trends.
- Strengthen marketing initiatives in underperforming regions.
- Monitor Budget vs Actual performance regularly to improve financial planning.
- Utilize customer segmentation for personalized marketing campaigns.
- Data Extraction
- Data Cleaning
- Data Transformation
- Joins
- CTEs
- CASE Statements
- Aggregations
- Power Query
- Data Modeling
- Star Schema Design
- DAX
- Dashboard Development
- Data Visualization
- KPI Reporting
- Sales Analytics
- Customer Analytics
- Revenue Analysis
- Business Intelligence
- Decision Support
- Data Storytelling
- SQL Scripts
- Data Warehouse Backup
- Power BI Dashboard (.pbix)
- Dashboard Screenshots
- Documentation
- README
This project demonstrates the complete Business Intelligence workflow by integrating SQL Server and Power BI to transform raw sales data into interactive dashboards and actionable business insights. It showcases practical experience in SQL development, data modeling, dashboard design, and analytical reporting, reflecting the skills required for Data Analyst, Business Intelligence Analyst, Reporting Analyst, MIS Analyst, and Business Analyst roles.
Model View
