Em Busca do Estado da Arte e da Práca sobre Schema Matching na Indústria Brasileira - Resultados Preliminares de uma Revisão de Literatura e uma Pesquisa de Opinião

Abstract

The integration of systems and interoperability between different databases are critical challenges in information technology, mainly due to the diversity of data schemas. The schema matching technique is essential for unifying these schemas, facilitating research, analysis, and knowledge discovery. This dissertation investigates the application of schema matching in the Brazilian software industry, focusing on understanding the reasons for its low adoption. The research included a systematic mapping of the use of Artificial Intelligence (AI) algorithms and similarity techniques in schema matching, as well as a survey with 35 professionals in the field. The results indicate that, although schema matching offers significant improvements in data integration processes, such as reducing time and increasing accuracy, most professionals are unfamiliar with the term, even among those who use similar tools. The low adoption of these techniques can be attributed to the lack of free or open source tools and the absence of implementation plans within companies. The dissertation highlights the need for initiatives that overcome these barriers, empower professionals, and promote broader use of schema matching in the Brazilian industry.