Design and implementation of a system of master tables for vehicle specifications

Identifier:  TFG:9486

Handle: https://hdl.handle.net/20.500.11797/TFG9486

Authors:  Salla Sendra, Roger

Abstract:
This project designs and implements an automated system to create and maintain master tables of vehicle brands and models. It includes a fully automated ETL process deployed on AWS and visualized with Qlik. The system is based on three pillars: data normalization using semantic algorithms and language models (LLM), automation with Lambda functions and AWS Step Functions, and validation with a real-world data cleansing case. The work applies mathematical and physical engineering knowledge in critical analysis, big data management, and complex problem solving.