The SusCity big data warehousing approach for smart cities

Nowadays, the concept of Smart City provides a rich analytical context, highlighting the need to store and process vast amounts of heterogeneous data flowing at different velocities. #is data is defined as Big Data, which imposes significant difficulties in traditional data techniques and technologi...

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Detalhes bibliográficos
Autor principal: Costa, Carlos (author)
Outros Autores: Santos, Maribel Yasmina (author)
Formato: conferencePaper
Idioma:eng
Publicado em: 2017
Assuntos:
Texto completo:http://hdl.handle.net/1822/46382
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/46382
Descrição
Resumo:Nowadays, the concept of Smart City provides a rich analytical context, highlighting the need to store and process vast amounts of heterogeneous data flowing at different velocities. #is data is defined as Big Data, which imposes significant difficulties in traditional data techniques and technologies. Data Warehouses (DWs) have long been recognized as a fundamental enterprise asset, providing fact-based decision support for several organizations. #e concept of DW is evolving. Traditionally, Relational Database Management Systems (RDBMSs) are used to store historical data, providing different analytical perspectives regarding several business processes. With the current advancements in Big Data techniques and technologies, the concept of Big Data Warehouse (BDW) emerges to surpass several limitations of traditional DWs. #is paper presents a novel approach for designing and implementing BDWs, which has been supporting the SusCity data visualization platform. #e BDW is a crucial component of the SusCity research project in the context of Smart Cities, supporting analytical tasks based on data collected in the city of Lisbon.