Vol.15, No.3, August 2026.                                                                                                                                                                          ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333

 

TEM Journal

 

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science

 

Assessing Readiness for Big Data Adoption: A Decision Support Model

 

Peter Procházka, Peter Schmidt, Ľudovít Pinda, Martin Mišút

 

© 2026 Peter Schmidt, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

 

Citation Information: TEM Journal. Volume 15, Issue 3, Pages 2168-2177, ISSN 2217-8309, DOI: 10.18421/TEM153-11, August 2026.

 

Received: 06 September 2025.
Revised: 07 January 2026.
Accepted: 02 March 2026.
Published: 27 August 2026.

 

Abstract:

 

This article addresses the challenges of implementing Big Data technologies in businesses and proposes a model to assess their readiness for such implementation. The authors identify key factors influencing the success of Big Data adoption, including data volume and growth, real-time analysis needs, competitive advantages, and return on investment. The proposed model uses Cosine similarity to compare company characteristics with those of a reference company. The article also discusses the challenges associated with Big Data implementation and emphasizes the importance of organizational culture and employee capabilities. The result is a flexible tool that allows managers to objectively assess their organization’s readiness for Big Data implementation and identify areas for improvement. The model contributes to more effective decision-making processes in the context of digital transformation and data-driven business strategies.

 

Keywords – Big Data, decision support, implementation readiness, organizational change, data analytics.

 

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