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The contribution of this paper is technology independent reference architecture for big data systems, which is based on analysis of published implementation architectures of big data use cases.
Stratos designs big data systems which are tailored for the new challenges posed by the big data era, i.e., systems that (a) are adaptive and easy to use by non experts, requiring minimum tuning and set-up effort and (b) can cope with the ever increasing rates of incoming data and the ever increasing demands for fast reactions to data searches.
The contribution of the paper is (an extended) RA design of metadata management layer for big data systems, which focuses on data quality management.
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There are other open source real-time big data systems, notably Storm, which was developed at Backtype and open sourced by Twitter, and Apache S4, which was open sourced by Yahoo.
The main contribution of this work is presentation of the metadata management layer for big data systems (Fig. 12), which has been validated with an implementation.
Variety Big data systems collect data stream from multiple data sources which produce data streams in multiple formats.
Velocity The velocity of big data is determined by the frequency of data streams which are entering in big data systems.
Facilitation type of RA was selected (step 1), which should provide guidelines for the design of similar big data systems.
We illustrate our approach for deriving the big data architectures of different well-known big data systems.
Finally, some case studies of exploiting big data systems for data management on WSNs are discussed.
It also attacks Facebook's analysis of users through what it calls "big data" systems.
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