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1. Introduction
1.1. Background

The application of Big Data (BD), Artificial Intelligence (AI) and

analytics has a critical role to play in the wine industry (covering the

whole wine life cycle) to streamline processes, increase process

efficiency, save money, provide decision making and grow. Mullen
(2020) defined viticulture as the study of vines and oenology as the

study of wines and the winemaking process. Whereas Market line

(2018) defined the wine wholesale industry as the sale of fortified,
sparkling and still wine.

Wang (2018) stated that in 2018, the Big Data industry was valued at

$122 billion dollars. PwC (2017) informed that by 2030 AI will
contribute $15.7 trillion to the global economy. Wood (2020) stated

that the global Big Data Analytics (BDA) market in 2018 was valued at

$37.34 billion dollars and by 2027 it is expected to reach $105.08

billion.

In 2023, the English wine markets forecasted a value of $25,192.9

million, an increasing by 16% since 2018. (Market line) 2018, pp.2.
Mullins (2020) informed that in 2018, Italy accounted for $6.22 billion

from the $32 billion of globally exported wine.

Sacolick (2017) states that BD is not defined by managerial issues but
by an organisational capacity for Data Analysis in-order to create

intelligent decisions which can be used to future looking decisions.

Mohammad et al (2020) defined Big Data into the three V model

(volume, velocity and variety). Big Data Volume defined as the volume
of data created that a mainframe must process daily. Mohammed et

al (2020) defined Velocity as the creation analysis and storage of

information. Ibid (2020) informed that roughly 80% to 90% of the

data Variety collected is in an unset format (text videos or censored
collected information). Complementary is Skanska (2018) who defined

Big Data as large amount, choices and speed of data creation. This
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