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Large-scale analytics is a key application area for data processing and parallel computing research.
OHDSI is a worldwide interdisciplinary program aiming to bring out the value of health data through large-scale analytics.
This, coupled with the computations that are often of interest in large-scale analytics applications, presents fundamental challenges to the way we think about efficient and meaningful computation in the era of large-scale data.
Large-Scale Analytics.
The experimentation reported in this work contributed mainly to the Large-Scale Analytics (LSA and Aviationn threads of Testbed-12.
While a single winner hasn't emerged in this, the trend feels pretty firmly set, and the overall "SQL-on-Hadoop" feels more and more like the new default for large-scale analytics data warehouses.
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In relation to our previous work [4, 10, 11], this paper offers the following unique contributions: (i) a complete description of the semantic type system of LooCI, (ii) a large-scale analytic evaluation and (iii) performance figures that quantify the overhead of semantics for two representative classes of WSN devices: AVR Raven [12] and Sun SPOT [15].
To discuss in deep the big data analytics, this paper gives not only a systematic description of traditional large-scale data analytics but also a detailed discussion about the differences between data and big data analytics framework for the data scientists or researchers to focus on the big data analytics.
He is particularly interested in designing algorithms and frameworks for large-scale graph analytics.
Many of the activities that large-scale data analytics now make possible are undoubtedly "legal" simply because our laws are so far behind the curve.
This paper describes Seeker, a platform for large-scale text analytics, and SemTag, an application written on the platform to perform automated semantic tagging of large corpora.
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