This project is a deep dive into the sales data of a fictional store, where I've leveraged a powerful trio of tools—Python, SQL, and Power BI—to uncover key business insights. The goal was to transform raw, messy data into a clear and compelling story about sales performance, customer behavior, and product trends.
I tackled the entire data pipeline, starting with data cleaning and transformation in Python. From there, I moved the cleaned data into a SQL database to perform targeted queries and exploratory analysis. The final and most exciting step was bringing it all to life in Power BI, where I designed and built interactive dashboards.
This repository contains all the components of my analysis, including:
- Python Scripts: The code I used to clean and preprocess the raw Excel data, making it ready for database import.
- SQL Queries: My collection of SQL scripts for extracting, aggregating, and analyzing the sales data to answer specific business questions.
- Power BI Dashboard: The complete
.pbixfile containing the interactive reports I built. The dashboard is divided into three key pages:- Sales Performance: A high-level overview of sales trends, profit margins, and key metrics.
- Customer Analysis: Insights into customer segmentation, purchasing habits, and lifetime value.
- Product Analysis: A look at top-selling products, category performance, and regional sales.
This project was a fantastic opportunity to apply my skills in data cleaning, SQL querying, and data visualization. I'm proud of the results and believe the final dashboards provide valuable, actionable insights.
Feel free to explore the code, queries, and reports. I'm always open to feedback and suggestions for improvement!