This analysis examines financial, educational, and demographic influences on divorce. It uncovers key trends, risk factors, and stability patterns using data analysis and machine learning.

This analysis delves into Spotify Albums Data, offering valuable insights into user engagement, album popularity, and listening trends over time

This project leverages SQL to analyze sales, customers, and products, uncovering key insights, trends, and performance patterns for data-driven decisions.

This project aims to analyze Netflix’s content catalog to uncover key insights into content distribution, genre trends, country contributions, and viewing patterns.

This analysis aims to examine Toman Bike Share’s data to uncover usage patterns, peak hours, and seasonal revenue fluctuations, enabling data-driven pricing strategies and improved operational decisions.

This analysis explores sales performance, revenue trends, and profitability across regions and discount strategies. By tracking YoY growth, discount impact, and seasonal revenue shifts, it helps businesses make data-driven decisions to optimize pricing and improve sales strategies.