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Data Collection Architecture for Big Data - A Framework for a Research Agenda
2015
International Workshop on Enterprise Interoperability
As big data is expected to contribute largely to economic growth, scalability of solutions becomes apparent for deployment by organisations. It requires automatic collection and processing of large, heterogeneous data sets of a variety of resources, dealing with various aspects like improving quality, fusion and linking data sets to provide homogeneous data to data analytics algorithms that are able to detect patterns or anomalies. This paper introduces two components in a data sharing
dblp:conf/ifip5-8/Hofman15
fatcat:5fxspsxzyffthh6css3ohzezba