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Divide and recombine (D&R): Data science for large complex data
Author(s) -
Cleveland William S.,
Hafen Ryan
Publication year - 2014
Publication title -
statistical analysis and data mining: the asa data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.381
H-Index - 33
eISSN - 1932-1872
pISSN - 1932-1864
DOI - 10.1002/sam.11242
Subject(s) - library science , citation , computer science , information retrieval
The need for deep analysis of large complex data has brought a focus to data science. The reasoning is simple. Data science consists of all technical areas that come into play in the analysis of data, and deep analysis of large complex data challenges all of the technical areas, from statistical theory to the architecture of clusters designed specifically for data. What is more, research in the technical areas needs to be tightly integrated.