Built a dimensional data warehouse on 60K+ sales transactions and 18K+ customers — designed fact/dimension tables and a centralized SQL reporting view to replace fragmented manual queries with a single business-ready analytics layer.

End-to-end Data Analytics project analyzing customer purchasing patterns using Python (EDA), SQL (PostgreSQL), and Power BI (Interactive Dashboards).

Market Basket Analysis

Understanding and forecasting online shoppers’ purchase behavior is crucial for e-commerce platforms aiming to improve personalization, marketing effectiveness, and customer retention. This study proposes a combined analytical framework integrating clustering and logistic regression

Churn Shield empowers B2B companies to: Predict customer churn in real-time using machine learning Analyze retention risks through an interactive dashboard Make data-driven decisions with stakeholders

End-to-end Customer Behaviour Analysis project with SQL insights, Python analytics, and interactive Power BI dashboards.

Customer Behavior Analysis | Data Analytics Project using Python, Pandas, Seaborn, and Exploratory Data Analysis (EDA).