A multilevel approach to big data analysis using analytic tools and actor network theory

South African Journal of Information Management

 
 
Field Value
 
Title A multilevel approach to big data analysis using analytic tools and actor network theory
 
Creator Iyamu, Tiko
 
Subject — actor network theory; analytics; big data; data analysis; information systems; multilevel
Description Background: Over the years, big data analytics has been statically carried out in a programmed way, which does not allow for translation of data sets from a subjective perspective. This approach affects an understanding of why and how data sets manifest themselves into various forms in the way that they do. This has a negative impact on the accuracy, redundancy and usefulness of data sets, which in turn affects the value of operations and the competitive effectiveness of an organisation. Also, the current single approach lacks a detailed examination of data sets, which big data deserve in order to improve purposefulness and usefulness.Objective: The purpose of this study was to propose a multilevel approach to big data analysis. This includes examining how a sociotechnical theory, the actor network theory (ANT), can be complementarily used with analytic tools for big data analysis.Method: In the study, the qualitative methods were employed from the interpretivist approach perspective.Results: From the findings, a framework that offers big data analytics at two levels, micro- (strategic) and macro- (operational) levels, was developed. Based on the framework, a model was developed, which can be used to guide the analysis of heterogeneous data sets that exist within networks.Conclusion: The multilevel approach ensures a fully detailed analysis, which is intended to increase accuracy, reduce redundancy and put the manipulation and manifestation of data sets into perspectives for improved organisations’ competitiveness.
 
Publisher AOSIS
 
Contributor
Date 2018-08-27
 
Type info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion — —
Format text/html application/epub+zip application/xml application/pdf
Identifier 10.4102/sajim.v20i1.914
 
Source SA Journal of Information Management; Vol 20, No 1 (2018); 9 pages 1560-683X 2078-1865
 
Language eng
 
Relation
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https://sajim.co.za/index.php/sajim/article/view/914/1303 https://sajim.co.za/index.php/sajim/article/view/914/1302 https://sajim.co.za/index.php/sajim/article/view/914/1304 https://sajim.co.za/index.php/sajim/article/view/914/1299
 
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Rights Copyright (c) 2018 Tiko Iyamu https://creativecommons.org/licenses/by/4.0
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