This project demonstrates an end-to-end data analytics workflow using SQL Server and Power BI. We take raw data from an Excel file, clean and structure it in SQL, and build an interactive Power BI dashboard to extract key business insights.
1️⃣ Data Preparation:
- Imported raw data from Excel into SQL Server
- Cleaned and structured data for analysis
2️⃣ SQL Data Processing:
- Created a relational database
- Used SQL queries to analyze revenue trends and customer behavior
3️⃣ Power BI Visualization:
- Built an interactive dashboard
- Presented insights on revenue trends, seasonality, and pricing impact
- SQL Server Management Studio (SSMS) – Data storage & querying
- Power BI – Data visualization & dashboard creation
- Excel & Flat Files – Raw data sources
- Seasonal demand fluctuations impact revenue.
- A 25% price increase led to higher revenue without reducing demand.
- Data-driven pricing strategies can optimize revenue without customer churn.
- Install SQL Server & SSMS
- Import the provided dataset (
.csvor.xlsx) into SQL - Run the SQL scripts to clean and structure data
- Execute SQL queries in
queries.sqlto extract insights
- Connect Power BI to SQL Server
- Use provided
.pbixfile to explore insights
📁 data/ - Raw dataset (Excel/CSV)
📁 sql_scripts/ - SQL queries & database setup
📁 powerbi_dashboard/ - Power BI report file
This project highlights how SQL and Power BI can be leveraged to make data-driven business decisions. If you're looking to improve your skills in business intelligence and data analytics, this is a great hands-on project to explore!
