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can be categorised as anticipated arrangements (such as the sensor
data) or disorganised arrangements (such as pictures or text). Casey

(2019) defined BD as reliant on AI to assist companies to achieve

unrealised methods for data storage which where nor previously
possible.

Hall and Pesenti (2020) defined AI as a series of progression in general

computerised technology which allow appliances to complete jobs
efficiently. Complementary Carmona (2019) defined AI as a use for

when machines executing tasks done by people. Whereas Patel (2020)

defined AI as cover term describing technology mirroring human

intelligence. AI is the use of a computer program or machine to learn.
AI is a field used to make consumers smart where computers work

individually without provided commands.

Simon (2017) defined analytics as the steps to use plain data to obtain
insights and improvement of the topic. AI informs individuals, groups

and organisations to improve and make better informed decisions by

embedding intuition with proof (evidence). The Alan Turing Institute

(2020) define Data Analytics as the steps used to change raw data to
suitable knowledge. Data Analytics consists of various stages and

phases, some stages of the data analysis procedure have been

improved by using software or tools. Maryvill (2020) stated that AI
and BD work cohesively because they are dependent on each another.

AI and computer learning learn from data to create rules to assist with

future analytical decisions.

1.2. Importance of study
Tivon (2019) indicated that the wine industry is taking advantage of

BD: analysing the performance of wine bottle labels to increase wine

sales; teaching computers to taste to predict wine that customers

would like prior to buying it. The wine industry applies wine sales trend
analysis (by time), profile customer behaviour, visualise it for specific

market and present it to distributors. This enabled wine organisations

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