Original Research

The architectures of data and information: Their confounded confusion

Tiko Iyamu
SA Journal of Information Management | Vol 21, No 1 | a1060 | DOI: https://doi.org/10.4102/sajim.v21i1.1060 | © 2019 Tiko Iyamu | This work is licensed under CC Attribution 4.0
Submitted: 25 November 2018 | Published: 29 August 2019

About the author(s)

Tiko Iyamu, Department of Information Technology, Faculty of Informatics and Design, Cape Peninsula University of Technology, District Six Campus, Cape Town, South Africa

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Background: Even though it is well documented in the academic domain, including various English dictionaries, that data and information are not the same thing, with the latter being a refinement of the former, many people within organisations and academic environments continue to loosely and interchangeably use these terms. This is a challenge that extends to the enterprise architecture discipline, which has an impact on how the domains of data and information architectures are defined, developed and implemented in many organisations.

Objectives: The challenge leads to misunderstanding of both technical and business requirements, as well as confusion about the differentiation between data and information architectures. This challenge affects the accomplishment of either data or information in an organisation. This is caused by the fact that data is referred to as information, meaning it has been refined, which is incorrect, and therefore affects requirements. Additionally, this challenge influences the organisational structure and the development of employees’ career. Thus, the objective of this study was to examine the implication of practice in the loose and interchangeable use of the terms, ‘data’ and ‘information’, within an organisation.

Method: Based on this objective, the interpretivist stance was employed in the study. Qualitative data was gathered and the hermeneutics approach was employed in the analysis.

Results: From the analysis, a solution is proposed to halt further misconstruction of the architectures, and avoid the confusing challenges it has for organisations.

Conclusion: The study reveals what we need to know about the confounded confusion between data and information architectures. The differentiation between the two concepts can be of importance to professionals in the field of information systems and technologies as well as academics.


Data architecture; information architecture; subjectivism; computing; information systems; qualitative methods.


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