Data Cleaning in SQL
This project demonstrates data cleaning techniques in SQL Server using the Nashville Housing dataset. The goal is to transform messy raw data into a clean, standardized, and more usable format for analysis
Data Cleaning in SQL
Coffee Shop Sales Analysis
Built an interactive Excel dashboard analyzing 6 months of coffee shop sales data across 3 NYC(New York City) locations. Identified peak transaction hours and top-performing products, leading to data-driven staffing and inventory recommendations that could reduce operational costs by 20%.
NBA-MVP-Analysis
This project explores over two decades of NBA player statistics to uncover trends in scoring, efficiency, and player development. Using SQL Server, the dataset was cleaned, transformed, and analyzed to identify top performers, rookie vs. veteran impact, and MVP-level seasons.
Toy Store KPI Dashboard
Developed a comprehensive Power BI dashboard for Maven Toys that consolidates 41,830 transactions across multiple store locations, featuring advanced DAX measures, interactive slicers, and time-series analysis to enable data-driven decision-making and reveal key insights such as the Toys category's dominance and revenue trends over an 18-month period.
Maven Sales Pipeline Analysis
This project focuses on analyzing MavenTech’s sales pipeline to provide the VP of Sales with deeper insights into team performance, helping identify strengths and weaknesses across the sales organization.
Player Statistics Analysis
This project contains a series of SQL queries exploring different aspects of baseball data, including schools, salaries, and player careers..
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