Abstract
Big data analytics (BDA) is constantly formulating decisions in agriculture and transforming the processes by which agriculture operates and controls. The agriculture process can be composed of a sequential flow of stages, starting from planting, spraying, fertilization, collection, and distribution to the end consumer. The variety within agriculture data is distinctly heterogeneous. This big farming data can come in all shapes and sizes from a variety of sources, which composes a hard analytical process for decision-makers. Big data analytical techniques have been applied to each stage in the agricultural operational process. These techniques have been proven to establish both economic gain for farmers and environmental and safety benefits for society at large. This chapter summarizes the state-of-art analytical methods that have been recently used in the agriculture industry, along with their financial and societal impacts.
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Kashef, R. (2020). Adopting Big Data Analysis in the Agricultural Sector: Financial and Societal Impacts. In: Pattnaik, P., Kumar, R., Pal, S. (eds) Internet of Things and Analytics for Agriculture, Volume 2. Studies in Big Data, vol 67. Springer, Singapore. https://doi.org/10.1007/978-981-15-0663-5_7
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