Analyze bank data to identify trustworthy loan applicants, aiming to reduce losses and enhance profitability through data-driven decision-making.

X Education needs to identify potential customers likely to enroll in their courses using data on customer behavior and demographics. With a dataset containing 37 factors, we'll clean the data and build a model to help the sales team target potential customers more effectively.

Developed a precise multiple linear regression model for a Bike Sharing Case Study, offering insights into demand variations based on various features and empowering management to tailor an effective business strategy to meet customer expectations.

The objective of the project is to track and improve the service levels by measuring:

On-time delivery (OT) %: The percentage of orders delivered on or before the promised date.

In-full delivery (IF) %: The percentage of orders delivered with the correct quantity as ordered.

On-time In-full (OTIF) %: The combined metric representing the percentage of orders delivered both on time and in full.

The aim of this project is to create an encompassing credit card weekly dashboard designed to offer real-time insights into crucial performance metrics and trends, facilitating stakeholders in the effective monitoring and analysis of credit card operations.

This project focuses on managing inventory costs by identifying top revenue-generating products and using Market Basket Analysis to understand customer purchase behavior. These insights will help improve inventory management, reduce holding costs, and optimize the stocking of high-demand products and complementary items.

This project employs Python, SQL, Excel, and Power BI for robust data analysis, leveraging their respective capabilities to extract, clean, analyze, and visualize data, enabling informed decision-making and strategic insights.

The main objective of this project is to provide a comprehensive overview of the performance of ATM network, enabling you to optimize for efficiency and make informed decisions.

The aim of this project is to focus on analyzing customers behavior and preferences within a banking context.

This objective of this project is to provide insights into loan approval trends and predict customer eligibility for loans based on various demographic and financial factors