Czech Bank Financial Data Dissection
Budget: ₹12,500 – ₹37,500 INR
### Czechoslovakia Banking Financial Data Analysis (Excel, MySQL & Power BI)
### Project Overview
An end-to-end financial data analysis executing advanced data transformation and business intelligence on 5 years of historical banking data from Czechoslovakia Bank. The project maps customer demographics, monitors year-over-year operational trends, evaluates product profitability (loans/credit cards), and assesses portfolio risk.
### Technical Execution & Workflow
* **Data Cleaning (Excel):** Performed extensive data quality checks, standardized conflicting date formats to YYYY-MM-DD, and normalized the timeline to modern parameters (+23-year shift).
* **Data Modeling & ETL (MySQL):** Designed and deployed a relational schema linking 8 complex transactional tables (Account, Disposition, District, Card, Client, Loan, Order, and Transaction) to manage heavy query operations.
* **Business Intelligence (Power BI):** Engineered fully interactive executive dashboards featuring advanced data modeling, complex measures, and seamless cross-filtering capabilities.
### Core Business Insights Delivered
* **Demographic Profiling:** Visualised client density and economic indicators across multiple geographical districts.
* **Trend Analysis:** Uncovered hidden performance loops via granular Year-over-Year (YoY) and Month-over-Month (MoM) revenue tracking.
* **Product Profitability:** Isolated highly active account categories and card tiers to track underlying utilization metrics.
* **Risk Engineering:** Built an active credit risk framework segmenting the bank’s outstanding loan portfolio against default probability vectors.
**GitHub Repository:** https://github.com/sairajdhanavade/czech-banking-financial-analysis
### Project Overview
An end-to-end financial data analysis executing advanced data transformation and business intelligence on 5 years of historical banking data from Czechoslovakia Bank. The project maps customer demographics, monitors year-over-year operational trends, evaluates product profitability (loans/credit cards), and assesses portfolio risk.
### Technical Execution & Workflow
* **Data Cleaning (Excel):** Performed extensive data quality checks, standardized conflicting date formats to YYYY-MM-DD, and normalized the timeline to modern parameters (+23-year shift).
* **Data Modeling & ETL (MySQL):** Designed and deployed a relational schema linking 8 complex transactional tables (Account, Disposition, District, Card, Client, Loan, Order, and Transaction) to manage heavy query operations.
* **Business Intelligence (Power BI):** Engineered fully interactive executive dashboards featuring advanced data modeling, complex measures, and seamless cross-filtering capabilities.
### Core Business Insights Delivered
* **Demographic Profiling:** Visualised client density and economic indicators across multiple geographical districts.
* **Trend Analysis:** Uncovered hidden performance loops via granular Year-over-Year (YoY) and Month-over-Month (MoM) revenue tracking.
* **Product Profitability:** Isolated highly active account categories and card tiers to track underlying utilization metrics.
* **Risk Engineering:** Built an active credit risk framework segmenting the bank’s outstanding loan portfolio against default probability vectors.
**GitHub Repository:** https://github.com/sairajdhanavade/czech-banking-financial-analysis