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Zwavhudi05/digital-banking-transaction-analytics

Domain:

socioeconomic

Record type:

dataset
Creator:
Zwa
Host:
End-to-end digital banking analytics project using PostgreSQL, SQL and Python, featuring 500,000 synthetic South African banking transactions, business analysis and query performance optimization. # Digital Banking Transaction Analytics ## Project Overview I built **Digital Banking Transaction Analytics** as an end-to-end SQL and data analytics portfolio project based on a simulated South African digital banking environment. My goal was to go beyond writing isolated SQL queries and build a complete workflow covering relational database design, synthetic data generation, data loading, validation, business analysis, debugging, and database performance investigation. I used Python to generate realistic synthetic banking data at scale, loaded the generated datasets into PostgreSQL, validated the data, analysed it using SQL, and investigated query performance using indexes and `EXPLAIN ANALYZE`. ### Dataset Size The final dataset contains: - 10,000 customers - 18,033 bank accounts - 295 merchants - 500,000 banking transactions - Multiple customer segments - Multiple transaction types - South African cities and provinces - Monetary values represented in South African Rand (ZAR) > **Note:** All customer, account, merchant, and transaction data in this project is synthetically generated. No real banking or personal information is used. --- ## Project Objectives I built this project to develop and demonstrate practical experience in: - Relational database design - PostgreSQL - SQL querying and analytics - Multi-table joins - Aggregate functions - Conditional aggregation - Common Table Expressions (CTEs) - Window functions - Data validation - Python-based synthetic data generation - CSV-based data pipelines - Database indexing - Query performance analysis - Debugging and problem solving - Translating business questions into SQL - Communicating analytical insights --- ## Technology Stack | Technology | Purpose | |---|---| | PostgreSQL | Relational database and analytical querying | | SQL | Database creation, loading, validation and analysis | | Python | Synthetic data generation | | CSV | Intermediate data storage | | Visual Studio Code | Development envi …