| Autor: |
Sarah Benjelloun, Mohamed El Mehdi El Aissi, Younes Lakhrissi, Safae El Haj Ben Ali |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Applied System Innovation, Vol 6, Iss 1, p 8 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2571-5577 |
| DOI: |
10.3390/asi6010008 |
| Popis: |
Thanks to continuously evolving data management solutions, data-driven strategies are considered the main success factor in many domains. These strategies consider data as the backbone, allowing advanced data analytics. However, in the agricultural field, and especially in fish farming, data-driven strategies have yet to be widely adopted. This research paper aims to demystify the situation of the fish farming domain in general by shedding light on big data generated in fish farms. The purpose is to propose a dedicated data lake functional architecture and extend it to a technical architecture to initiate a fish farming data-driven strategy. The research opted for an exploratory study to explore the existing big data technologies and to propose an architecture applicable to the fish farming data-driven strategy. The paper provides a review of how big data technologies offer multiple advantages for decision making and enabling prediction use cases. It also highlights different big data technologies and their use. Finally, the paper presents the proposed architecture to initiate a data-driven strategy in the fish farming domain. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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