projects
1. Analysis of Sales Information
determined trends and patterns by analyzing sales data for a retail business.
Data processing, cleaning, and visualization were done using Python (Pandas) and Excel.
To display important data including sales success, regional trends, and product popularity, interactive dashboards were made in Tableau.
Due to well-informed decision-making, operational efficiency increased by 10%.
2. Analytics for Customer Churn Prediction
Using Python (Scikit-learn), a predictive model was created to forecast client attrition based on past data.
utilized logistic regression for classification, cleaned and preprocessed the data, and conducted exploratory data analysis (EDA).
presented findings via a Power BI dashboard, assisting the marketing team in lowering attrition through the application of focused tactics.
