Big Data Enabling Fish Farming Data-Driven Strategy

• Published in: Ingénierie des systèmes d'Information 2022-12, Vol.27 (6), p.949-956
• Main Authors: El Aissi, Mohamed El Mehdi, Benjelloun, Sarah, Lakhrissi, Younes, El Haj Ben Ali, Safae
• Format: Article
• Language: English
• Subjects: Aquaculture; Artificial intelligence; Automation; Big Data; Data processing; Data warehouses; Domains; Employment; Farms; Fish; Fish production; Fisheries; Fishing; Food safety; Population growth; Sustainability; Water quality
• ISSN: 1633-1311; 2116-7125
• DOI: 10.18280/isi.270611

The last two decades have witnessed an exponential data generation in tremendous amounts. The digital transformation in many domains leads to massive amounts of heterogeneous data. In order to benefit from this generation, value is extracted through data processing. Meanwhile, the fish farming functioning activity generates data with such volume, speed, heterogeneous sources and structures but it is not fully exploited. The traditional data warehouse solutions are not able to manage complex data with these characteristics. Thus, the concept of the data lake has emerged for more flexible and powerful data exploitation. Indeed, big data technologies and techniques are used to extract, process and analyze data. Since big data technologies have proved their benefits in other domains, it is irrefutable that using them in the fish farming domain will help it to reach its full potential. For this purpose, we propose in this paper a dedicated data lake architecture for handling fish farming data to initiate the adoption of a data driven strategy.