Formation of Components of the Marketing Information System for Agricultural Products Using Big Data Methods
Journal Title: Oblik i finansi - Year 2023, Vol 1, Issue 3
Abstract
Big data is a source of innovation. Big data helps companies in various fields move towards digital transformation. The purpose of the article is to reveal the possibilities of using big data methods in marketing agricultural products to increase production efficiency, support the agricultural economy, and develop information marketing systems. The research identifies the possibilities of creating intelligent marketing systems based on big data; evaluates the technological challenges associated with collecting, storing and analysing large volumes of data in real-time; studies the localisation of data and the possibilities of their use to support the agricultural sector in the regions. Intelligent marketing creates both great opportunities and challenges for data analysis. Significant challenges include extensive samples and high dimensionality of the data, missing data and noise, and low data reliability. In addition, with the complex internal structure of the information system, the analysis of collected data becomes more time-consuming, requiring innovative data processing methods. At the same time, thanks to the intelligent marketing data processing centre, it is possible to control the regional circulation of agricultural products, their quality and safety, and prices, and react to sudden changes in the market in real-time. The article presents the idea of a big data centre for intelligent marketing of agricultural products. The components of the block of service provision using big data methods were described. The study results indicate that for the further development of the marketing of agricultural products using big data methods, it is crucial to develop the components of the marketing information system, ensure the accuracy and timeliness of marketing information, integrate data from various sources, and also support constant analysis and correction of strategies based on the collected data.
Authors and Affiliations
Oleksandr LutsiŃ– & Oleksandr Helevei
Keywords
Related Articles
- EP ID EP725113
- DOI 10.33146/2307-9878-2023-3(101)-145-151
- Views 51
- Downloads 0
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