Big data and data science

conceptual complementarity in the decision-making process

Authors

DOI:

https://doi.org/10.36311/1981-1640.2019.v13n1.06.p56

Keywords:

Big Data, Data Science, Decision-Making Process, Knowledge-Intensive Tasks

Abstract

Nowadays, huge databases are produced in a wide range of domains due to the evolution and the massive use of the Information and Communication Technologies. Therefore, the development of instruments for extracting information from Big Data and fostering actionable knowledge in Decision-Making Processes arise interest by several organizations. In this context, the evolution of data ? information ? knowledge requires the synergy of competences in a new domain, the Data Science. Among the activities of that domain, can be cited: obtaining data from various sources distributed on the web; creating models for handling data and metadata; and planning the exploration of data and metadata to produce relevant information in Decision-Making Processes. Considering these statements, this paper aims to discuss the difference and the complementarity between the Big Data and Data Science concepts. As a result, it is pointed out that Big Data delineates the cloud computing services for storing, processing and distributing data resources. Regarding to Data Science, it is a concept related to the use of software for transforming data into information, supporting the decision makers when dealing with the Knowledge-Intensive Tasks.

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Published

2019-03-29

Issue

Vol. 13 No. 1 (2019)

Section

Papers

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How to Cite

“Big Data and Data Science: Conceptual Complementarity in the Decision-Making Process”. Brazilian Journal of Information Science: Research Trends, vol. 13, no. 1, Mar. 2019, pp. 56-67, https://doi.org/10.36311/1981-1640.2019.v13n1.06.p56.