Game Data Analytics Pipeline

ETL Pipeline: Crawled game data from sources such as Steam, Epic Games, and game review websites, storing it in PostgreSQL/MongoDB. Processed and cleaned large datasets using PySpark for standardization and aggregation.

Data Warehouse & Dashboard: Designed a Data Warehouse for game information (title, publisher, genre, price, rating, user reviews). Transformed data using dbt and created interactive dashboards on Power BI, enabling analysis of game release trends, price comparisons, genres, and user ratings.