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Data Value, Big Data Analytics, and Decision-Making

Author

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  • Jean-Louis Monino

    (Université de Montpellier)

Abstract

With the increasing integration of different technologies in a growing range of equipment and products, big data is a paradigm shift that involves data analysis, using well-known schemes, to extract patterns in hidden relationships. This is the radical change in the “business model” of a company related to the monetization of the data it collects. The biggest question for a company is no longer deciding if it should launch new products, but rather taking advantage of available (structured or unstructured) data and to know how to develop a high performance and design an appropriate mining to efficiently analyze big data and to find the useful things from it. The objective of this paper is to show that the challenges of the era of “data revolution” focus on data uses. It is linked to the rise of the intangible economy that mobilizes knowledge and highlights the importance of data. To deeply discuss this issue, this paper illustrates the buzz words related to data especially big data and open data, in order to illuminate the discussions of data valorization.

Suggested Citation

  • Jean-Louis Monino, 2021. "Data Value, Big Data Analytics, and Decision-Making," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(1), pages 256-267, March.
    • Handle: RePEc:spr:jknowl:v:12:y:2021:i:1:d:10.1007_s13132-016-0396-2
    DOI: 10.1007/s13132-016-0396-2
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    Cited by:

    1. Claire Jean-Quartier & Miguel Rey Mazón & Mario Lovrić & Sarah Stryeck, 2022. "Collaborative Data Use between Private and Public Stakeholders—A Regional Case Study," Data, MDPI, vol. 7(2), pages 1-14, January.
    2. Chi-hsiang Chen, 2024. "Influence of Employees’ Intention to Adopt AI Applications and Big Data Analytical Capability on Operational Performance in the High-Tech Firms," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 3946-3974, March.

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