| Literature DB >> 28918390 |
Daniel Fuller1, Richard Buote2, Kevin Stanley3.
Abstract
The volume and velocity of data are growing rapidly and big data analytics are being applied to these data in many fields. Population and public health researchers may be unfamiliar with the terminology and statistical methods used in big data. This creates a barrier to the application of big data analytics. The purpose of this glossary is to define terms used in big data and big data analytics and to contextualise these terms. We define the five Vs of big data and provide definitions and distinctions for data mining, machine learning and deep learning, among other terms. We provide key distinctions between big data and statistical analysis methods applied to big data. We contextualise the glossary by providing examples where big data analysis methods have been applied to population and public health research problems and provide brief guidance on how to learn big data analysis methods. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.Entities:
Keywords: methodology; public health; research methods
Mesh:
Year: 2017 PMID: 28918390 DOI: 10.1136/jech-2017-209608
Source DB: PubMed Journal: J Epidemiol Community Health ISSN: 0143-005X Impact factor: 3.710