The logical differentiation between small data and big data

South African Journal of Information Management

 
 
Field Value
 
Title The logical differentiation between small data and big data
 
Creator Nyikana, Wandisa Iyamu, Tiko
 
Subject — big data; confusion between small and big data; taxonomic; small data; data differentiation; data classification; data nomenclature; data characteristics; logic difference; data analytics
Description Background: The distinction between small data and big data is increasingly muted and has caused challenges and confusion in many quarters.Objective: The objective of the study is to gain a deeper understanding of the confounded confusion that exists between small data and big data. Firstly, to develop a taxonomy that distinguishes between small data and big data. Secondly, it seeks to extract the value from the concepts, which can be of fundamental importance to an organisation.Methods: This study follows the interpretive approach and employs qualitative methods, based on which 57 related materials were gathered, covering big data and small data, and analysed.Results: The study reveals the factors that differentiate the concepts, which are of a technical front, business logic and data processing.Conclusion: This study addresses the challenges which are increasingly of prohibitive ramifications for both academic and business domains. By removing the confusion, the classifications of small data and big data including associated attributes will be better understood. This increases their business use towards enhancement and competitive advantage.Contribution: The article distinguishes between small data and big data, which has been missing, from both academic and business perspectives, since the emergence of the latter. The differentiation between small data and big data provides a guide to organisations in developing strategic frameworks and operational plans.
 
Publisher AOSIS
 
Contributor
Date 2023-12-24
 
Type info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion — —
Format text/html application/epub+zip text/xml application/pdf
Identifier 10.4102/sajim.v25i1.1701
 
Source South African Journal of Information Management; Vol 25, No 1 (2023); 9 pages 1560-683X 2078-1865
 
Language eng
 
Relation
The following web links (URLs) may trigger a file download or direct you to an alternative webpage to gain access to a publication file format of the published article:

https://sajim.co.za/index.php/sajim/article/view/1701/2535 https://sajim.co.za/index.php/sajim/article/view/1701/2536 https://sajim.co.za/index.php/sajim/article/view/1701/2537 https://sajim.co.za/index.php/sajim/article/view/1701/2538
 
Coverage — — —
Rights Copyright (c) 2023 Wandisa Nyikana, Tiko Iyamu https://creativecommons.org/licenses/by/4.0
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