A comprehensive Banking Data Analytics Project designed to transform raw transaction data into meaningful insights using Excel, Power BI, Tableau, and MySQL. The project focuses on credit/debit transaction analysis, customer behavior, and financial reporting, providing an end-to-end data journey from data cleaning to interactive dashboards.
Collect, clean, and analyze raw banking data.
Perform SQL-based querying for deep insights.
Build dashboards to visualize:
Credit & Debit transaction trends
Customer behavior & spending patterns
Monthly/Yearly financial performance
Enable data-driven decision making in the banking sector.
✔️ SQL Data Analysis – Queries to extract, aggregate, and filter transaction insights. ✔️ Excel Dashboards – Pivot tables, charts, and KPI tracking. ✔️ Power BI Reports – Interactive reports with filters and slicers. ✔️ Tableau Visualizations – Advanced storytelling dashboards. ✔️ End-to-End Workflow – From raw data → SQL processing → visualization.
MySQL – Data storage, querying, and preprocessing.
Excel – Data cleaning, pivot charts, dashboard creation.
Power BI – Interactive analytics and visualization.
Tableau – Advanced data visualization and insights.
- Excel:
- Designed an Excel Banking Dashboard to track loan performance, customer transactions, and account balance trends, providing actionable insights for financial analysis.
- PowerBI:
- Developed an interactive Power BI Loan Summary Dashboard with drill-down analysis on loan trends, recovery performance, and borrower demographics to support data-driven financial decisions.
- Tableau:
- Designed a Tableau dashboard to analyze debit and credit performance across banks, branches, and customers. The dashboard highlights transaction trends, customer insights, and payment methods to support financial decision-making.
Helps financial analysts track credit/debit patterns.
Provides management dashboards for strategic decision making.
Useful for students & professionals to learn multi-tool analytics.
Can be extended for fraud detection, risk analysis, and forecasting.
Automating SQL data pipeline with Python/ETL tools.
Adding Machine Learning models for fraud detection & predictions.
Expanding dataset for real-world banking case studies.
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Elluri Imran
📌 GitHub Profile
✨ This project demonstrates how Banking data can be transformed into actionable insights using multiple BI tools.
