Big Data Application: Analyzing Amazon's Recommendation System

This report delves into Amazon's strategic application of big data to enhance its recommendation system. It highlights how Amazon collects and utilizes vast amounts of customer data, including search history, personal details, and browsing behavior, to predict consumer needs and personalize product ...Read More

Big Data

INTRODUCTION
The term "big data" refers to a technology that aids in the management of massive amounts of data.
Data collecting is being digitized in today's world, when practically everything has gone digital. A
company's data refers to all of the important information it has about its consumers, market insights,
and even its competitors' marketing efforts. All of this information is examined and used to develop
strategies (Chen and et. al., 2018). In this report, Amazon's recommendation system makes use of its
data. When a user searches for a specific product, this information aids the platform in determining
what else the person might be interested in. Amazon is a pacesetter in collecting, storing, processing
and studying non-public records from each purchaser as a way of figuring out how clients are
spending their money. The organization makes use of predictive analytics for centered advertising
which allows them in growing purchaser pleasure and get loyalty in return.

Big Data Functions Used by Amazon
• Uses recommendation based system (RBS): Through this technology, it gathers statistics from their
clients (Can additionally be referred to as Big Data). The extra statistics they have got the higher it's
miles for them due to the fact after they apprehend what the consumer wants, they then streamline the
technique and try and inspire the clients to buy the goods. RBS seeks and predicts the rating or
preference a consumer could deliver to an item. Data technology allows Amazon to apprehend the
desires and as opposed to the clients attempting to find comparable merchandise, it presents the goods
with inside the recommendation. This is completed with the assist of collaborative filtering. It attempts
to construct a profile of you whilst you look for the goods. It has many such profiles and thru the assist
of collaborative filtering, it serves you with the product that comparable profile humans have purchased.

Big Data Functions Used by Amazon
• Tracking the user to understand the mind-set: It
has track of almost about everything- beginning out of
your desires, what you've got searched, what you'll
want in future, your non-public details (like touch
range and cope with) and thru the cope with it
additionally attempts to apprehend the earnings degree
of the consumer, in order that it may apprehend what
merchandise to provide and what not (Dev and et. al.,
2019). It additionally continues a test at the comments
behaviour and research that as well.

Big Data Functions Used by Amazon
• Understands the technicalities: Amazon
attempts to apprehend the behaviour and the time
one devotes to every platform for browsing. The
outside database is likewise being used. All that is
dealt with from its principal statistics warehouse
of Amazon.

Big Data Functions Used by Amazon
• Faster process of shipping: Amazon has made the technique of delivery lots easier. Through the
assist of huge statistics analytics insights, it has reached thru a role in which it may are expecting
who will order what and when (Ed-Daoudy and Maalmi, 2019). This has multiplied the enjoy of
on-line shopping.

CONCLUSION
It has been concluded from the summary that the approaches in which Amazon is
accumulating and enforcing large statistics to pressure greater client traffic. The procedure
of records collection starts proper from the moment someone navigates the website.
Nowadays, we will see it occurring so often. We look for a product at the platform and its
commercials begin to come earlier than us at each viable place. Technology is converting
the dynamics of the whole thing and agencies aren't any exception. Amazon is a massive
in the e-trade platform and now we realize the reason, clever use of technology.

REFERENCES
Books and Journals
Chen, C. and et. al., 2018. Flinkcl: An opencl-based in-memory computing architecture on
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1779.
Côrte-Real, N., Ruivo, P. and Oliveira, T., 2020. Leveraging internet of things and big data analytics
initiatives in European and American firms: Is data quality a way to extract business
value? Information & Management. 57(1). p.103141.
Dev, N.K. and et. al., 2019. Multi-criteria evaluation of real-time key performance indicators of
supply chain with consideration of big data architecture. Computers & Industrial Engineering. 128.
pp.1076-1087.
Ed-Daoudy, A. and Maalmi, K., 2019, April. Real-time machine learning for early detection of heart
disease using big data approach. In 2019 international conference on wireless technologies,
embedded and intelligent systems (WITS). (pp. 1-5). IEEE.
Elia, G. and et. al., 2020. A multi-dimension framework for value creation through big
data. Industrial Marketing Management. 90. pp.617-632.