Ejup Rustemi1*, Mefail Tahiri2
1University of Tetova, North Macedonia
2University of Tetova, North Macedonia
*ejup.rustemi@yahoo.com
ABSTRACT
Our society is governed by data. The digital revolution, characterized by the everyday generation of vast quantities of data, stems from the pursuit of innovative solutions and competitive advantage. The processing and analysis of this extensive data set, collected from many sources and containing inconsistent, erroneous, inadequate, and misleading information, poses considerable hurdles for contemporary enterprises. The diversity of data sources, including text, graphics, audio, and video, along with the rapid generation, collection, and processing of real-time data, contributes to significant complexity within these databases. To evaluate this vast volume of structured and unstructured data, novel data analytics patterns and trends are necessary. Big Data constitutes an extensive aggregation of information-dense data that may be broadly classified into five dimensions: I volume: delineating the data’s considerable magnitude; Velocity: the speed at which fresh data is produced and assessed in real time; (ii) Variety: denoting unstructured data from diverse sources, including traditional databases, transactional systems, the Internet, and social media; (iii) Veracity: the authenticity or provenance of the data; and (iv) Value: the worth of the data, contingent upon whether it is historical or contemporary. This paper will underscore the significance and problems of data science within the business environment.
Keywords: data, data science, business, strategy, big data.
Volume 10, No.1 (2025): April
ISSN 2661-2666 (Online) International Scientific Journal Monte (ISJM)
ISSN 2661-264X (Print)
DOI : 10.33807/monte.20253299
DOI URL: https://doi.org/10.33807/monte.20253299
Full Text: PDF
This is an open-access article under the CC BY-NC-ND license (creativecommons.org/licenses/by-nc-nd/4.0/)