Brum, Luciano Moraes da Luz and Lampert, Vinícius do Nascimento and Camargo, Sandro da Silva (2019) Business Intelligence and Data Warehouse in Agrarian Sector: A Bibliometric Study. Journal of Agricultural Science, 11 (2). p. 353. ISSN 1916-9752
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Abstract
Business Intelligence with Data Warehouse technologies are known in the literature as solutions that allow access to business data dynamically and analytical operations on them. Scientific literature lacks works that investigate the current use of these technologies in the agrarian sector, at the international level in the last 10 years. This work presents a bibliometric analysis, which was done through the ProKnow-C methodology, of the application of Business Intelligence and Data Warehouse technologies in the agrarian sector. The objective is to investigate the dissemination of such technologies in this sector in national and international scale. The main findings were the following: number of papers in last years are increasing. Majority of papers were found in the journal named Computers and Eletronics in Agriculture, with a great number of colaborations between authors of France. Few colaborations between authors from different countries were found. Sandro Bimonte was the most cited author. France and India highlight in researches approaching Data Warehouse and Business Intelligence usage in agrarian sciences. The majority of references from Bibliographic Portfolio were from 2001-2010. 66% of papers use some open source technology. Star schema is the most used modelling technique and the use of Unified Modeling Language by authors of France in agricultural Data Warehouse modelling is encouraged. The main limitations were the impossibility of free access in some databases, absence of research on proprietary solutions of technology market in the rural sector and few number of keyword searches.
Item Type: | Article |
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Subjects: | Universal Eprints > Agricultural and Food Science |
Depositing User: | Managing Editor |
Date Deposited: | 10 May 2023 04:49 |
Last Modified: | 20 Jan 2024 10:10 |
URI: | http://journal.article2publish.com/id/eprint/1902 |