Version 1
: Received: 18 August 2018 / Approved: 18 August 2018 / Online: 18 August 2018 (11:05:24 CEST)
How to cite:
Olszak, C.M.; Mach-Król, M. Conceptual Framework for Assessing Organization’s Readiness to Big Data Adoption. Preprints2018, 2018080335. https://doi.org/10.20944/preprints201808.0335.v1
Olszak, C.M.; Mach-Król, M. Conceptual Framework for Assessing Organization’s Readiness to Big Data Adoption. Preprints 2018, 2018080335. https://doi.org/10.20944/preprints201808.0335.v1
Olszak, C.M.; Mach-Król, M. Conceptual Framework for Assessing Organization’s Readiness to Big Data Adoption. Preprints2018, 2018080335. https://doi.org/10.20944/preprints201808.0335.v1
APA Style
Olszak, C.M., & Mach-Król, M. (2018). Conceptual Framework for Assessing Organization’s Readiness to Big Data Adoption. Preprints. https://doi.org/10.20944/preprints201808.0335.v1
Chicago/Turabian Style
Olszak, C.M. and Maria Mach-Król. 2018 "Conceptual Framework for Assessing Organization’s Readiness to Big Data Adoption" Preprints. https://doi.org/10.20944/preprints201808.0335.v1
Abstract
The main aim of this paper is to explore the issue of big data and to propose a conceptual framework for big data, based on the temporal dimension. The Temporal Big Data Maturity Model (TBDMM) is a means for assessing organization’s readiness to fully profit from big data analysis. It allows the measurement of the current state of the organization’s big data assets and analytical tools, and to plan their future development. The framework explicitly incorporates a time dimension, providing a complete means for assessing also the readiness to process temporal data and/or knowledge that can be found in modern sources, such as big data ones. Temporality in the proposed framework extends and enhances the already existing maturity models for big data. This research paper is based on a critical analysis of literature, as well as creative thinking, and on the case-study approach involving multiple cases. The literature-based research has shown that the existing maturity models for big data do not treat the temporal dimension as the basic one. At the same time, dynamic analytics is crucial for a sustainable competitive advantage. This conceptual framework was well received among practitioners, to whom it has been presented during interviews. The participants in the consultations often expressed their need of temporal big data analytics, and hence the temporal approach of the maturity model was widely welcomed.
Keywords
big data; maturity model; temporal analytics; advanced business analytics
Subject
Business, Economics and Management, Business and Management
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
