• Informações do Trabalho

Titulo Stream and Historical Data Integration using SQL as Standard Language Subtítulo Autor JEFFERSON DO NASCIMENTO AMARÁ Orientador VICTOR STROELE DE ANDRADE MENEZES Resumo Volume, Velocity, Variety, Veracity, and Value of data have, in addition to help define the meaning of the term Big Data, become part of the reality of systems that deal with data stream produced by IoT devices. In this context, data heterogeneity presents itself as a challenge for these systems concerning integrating and monitoring this data. The complexity imposed by data heterogeneity makes it difficult to integrate 'streaming x streaming' and 'streaming x historical' data types. For practical analysis, the enrichment and contextualization process based on historical and streaming data would benefit from approaches that facilitate data integration, abstracting from the analyses the details and format of these primary sources. This work presents a framework that allows the integration of streaming data and historical data in real-time, abstracting from the user syntactic aspects of queries through the use of SQL as a standard language for querying heterogeneous data sources. The framework was evaluated through an experiment using relational databases and real data produced by sensors. The results point to the feasibility of the approach. Palavras-Chave Heterogeneous Data, Data Integration, Data Streaming, SQL