Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/46382

TitleThe SusCity big data warehousing approach for smart cities
Author(s)Costa, Carlos
Santos, Maribel Yasmina
KeywordsBig Data
Big Data Warehousing
Hadoop
NoSQL
Data Warehouse
Smart Cities
Issue dateJul-2017
PublisherAssociation for Computing Machinery (ACM)
CitationCosta, Carlos, and Maribel Yasmina Santos, “The SusCity Big Data Warehousing Approach for Smart Cities”. In Proceedings of International Database Engineering & Applications Symposium (IDEAS’17), Bristol, United Kingdom, 12-14 July, 2017, pp. 264-273. DOI: 10.1145/3105831.3105841
Abstract(s)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.
TypeConference paper
URIhttp://hdl.handle.net/1822/46382
ISBN9781450352208
DOI10.1145/3105831.3105841
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

Files in This Item:
File Description SizeFormat 
IDEAS_2017_CC_MYS.pdf
  Restricted access
2,09 MBAdobe PDFView/Open    Request a copy!

This item is licensed under a Creative Commons License Creative Commons

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID