Welcome to the Bank Loan Data Analysis project repository. This project explores a dataset related to bank loans, aiming to derive insights and make data-driven decisions.
In this project, we analyze a dataset containing information about bank loans. The primary objectives include understanding the characteristics of borrowers, assessing risk factors, and gaining insights into the loan approval process.
DataBase Language: SQL
Server: Microsoft SQL Server Management Studio 2019
What I Learned:
SQL Proficiency: Strengthened my SQL skills by working extensively with complex queries, aggregations, and data manipulation.
Data Exploration: Gained experience in exploring and understanding a dataset, identifying key features, and extracting meaningful insights.
Risk Assessment: Developed a deeper understanding of risk factors in the context of loan approval, particularly regarding credit scores and interest rates.
Challenges Faced and Solutions:
Data Quality: Dealing with missing or inconsistent data. I addressed this by carefully cleaning and preprocessing the data, filling missing values, and handling outliers.
Performance Optimization: When working with large datasets, optimizing SQL queries for performance can be a challenge. I optimized queries by indexing columns and utilizing query execution plans.
Understanding Business Context: Understanding the domain-specific nuances of the banking and loan industry was a challenge. I overcame this by conducting research, consulting domain experts, and seeking feedback.
This project serves as a foundation for further analysis. Future work may include predictive modeling, additional feature engineering, and exploring external factors influencing loan approval.
For any questions or collaboration opportunities, feel free to reach out:
- Email: [email protected]
- LinkedIn: https://www.linkedin.com/in/your-linkedin-profile/](https://www.linkedin.com/in/vikas-bhat-a89635116/
Thank you for exploring the Bank Loan Data Analysis project!
Vikas Bhat.