In:
it - Information Technology, Walter de Gruyter GmbH, Vol. 58, No. 4 ( 2016-8-28), p. 176-185
Abstract:
Big Data and Big Data analytics have attracted major interest in research and industry and continue to do so. The high
demand for capable and scalable analytics in combination with the ever increasing number and volume of application scenarios and data has lead to a large and intransparent landscape full of versions, variants and individual
algorithms. As this zoo of methods lacks a systematic way of description, understanding is almost impossible which severely hinders effective application and efficient development of analytic algorithms. To solve this issue we propose
our concept of modular analytics that abstracts the essentials of an analytic domain and turns them into a set of universal building blocks. As arbitrary algorithms can be created from the same set of blocks, understanding is eased and
development benefits from reusability.
Type of Medium:
Online Resource
ISSN:
1611-2776
,
2196-7032
DOI:
10.1515/itit-2016-0003
Language:
English
Publisher:
Walter de Gruyter GmbH
Publication Date:
2016
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2102301-3
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144419-0
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165820-7
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2028598-X
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6242-X
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1146417-3
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