Banking Risk Analysis Dashboard
An end-to-end Data Analysis project showcasing a complete data journey—from Python EDA to an interactive Power BI Dashboard.
Project Overview
This project showcases a complete data journey in the Banking domain—from Exploratory Data Analysis (EDA) in Python to an interactive Power BI Dashboard designed to uncover meaningful insights in banking operations and risk assessment.
Data Pipeline
The workflow spans across raw data processing to final visual storytelling:
Raw Data
CSV Extraction
Python EDA
Pandas & Cleaning
Data Modeling
Power BI DAX
Dashboard
Interactive Insights
Dashboard Pages
Built an interactive and user-friendly dashboard divided into 5 key pages:
Home – Quick overview and navigation menu.
Loan Analysis – Trends, types, and high-risk lending areas.
Deposit Analysis – Patterns, customer segments, and growth metrics.
Summary – Key metrics and actionable insights.
Ask a Question – Natural language Q&A feature using Power BI's AI capabilities.
Tools & Skills
This project sharpened skills in both technical analysis and visual storytelling:
Python (Pandas, Seaborn, Matplotlib) for EDA.
Power BI (DAX, Data Modeling, AI Visuals) for BI.
Data Cleaning & Transformation pipelines.
Domain Understanding – Banking & Financial Services.
Project Demo
Project Note
Download the PBIX file and dataset from GitHub to explore the complete dashboard locally in Power BI Desktop.