Amazon's Use of Data Analytics, Big Data, and Tech for Efficiency

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This report explores Amazon Inc.'s utilization of Big Data Analytics to manage and leverage its vast data resources for informed business decisions and enhanced customer experience. It identifies the problems associated with overwhelming data, particularly in the context of Amazon's extensive product and service offerings, and discusses the implementation of collaborative filtering technology to fine-tune the recommendation engine. Key metrics for defining the problem include customer feedback and usability of the website. Methods to analyze the data involve building virtual customer profiles based on behavior and surfing patterns. The report also highlights the use of Lean Dashboards for data visualization and identifies key stakeholders, including business executives, board members, data analysts, decision-making bodies, and customers. Ultimately, the analysis aims to improve customer satisfaction by providing better-informed buying and selling suggestions, while also bringing in new potential customers. The report also touches on the factors influencing decision-making and potential challenges in implementing these solutions.
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Running head: DATA ANALYTICS, BIG DATA AND TECHNOLOGY
Data Analytics, Big Data and Technology
Name of the Student
Name of the University
Author Note
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1DATA ANALYTICS, BIG DATA AND TECHNOLOGY
Table of Contents
Introduction................................................................................................................................2
Identification of the organization...........................................................................................2
Problem or potential of efficiency..........................................................................................3
Key metrics to define the problem.........................................................................................5
Methods to analyse the data generated in the organization....................................................5
Example of the inclusion of a dashboard...............................................................................6
Identification of the key stakeholders....................................................................................7
Organizational benefits as per the analysis of the data..........................................................7
Factors that influence the decision-making process by data analysis....................................8
Challenges in the implementation of the solution..................................................................8
Reflection about the data analytics........................................................................................8
Conclusion..................................................................................................................................9
References................................................................................................................................10
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2DATA ANALYTICS, BIG DATA AND TECHNOLOGY
Introduction
The utilization of the Big Data analytics has been found to be a complex system that
is used for the examination of huge amount of data and processing of the varied amount of
data sets for finding out the hidden patterns in the generated data. These have been utilized
for the purpose of businesses as well. Often the data is utilized and the benefits of the big data
analytics are used by the organizations to find out the unknown correlations and the market
trends to be found out in the data and information generated in the business (Bell 2015).
Mostly, it has been found that the utilization of the Data and Business Analytics have been
focused on finding out the relations between the data to help in generating informed business
decisions. Therefore, the following report is being utilized for finding out the use of the Big
Data Analytics identifying the organization or Amazon Inc. and their utilization of the
business data with Big Data Analytics technique. This would be further utilized for the
methods that the organization uses for the data analysis and all the processes that makes sure
about the factors that the organization considers before the results of the analysis influences
the decision-making procedure.
Identification of the organization
Amazon Inc. is a well-established multinational American organization that is mostly
based up on the technology. The company is established in Seattle, Washington and it has its
entire focus on the settlement of e-commerce systems, the utilization of Cloud Computing in
business, streaming over digital platforms and the use of the artificial intelligence in business.
Amazon has even become one of the most influential technology companies that is based up
on the internet. It is also considered to be one of the Big Four organizations based on
technology, the other three including Apple, Google and Facebook (Barga 2016). Amazon
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3DATA ANALYTICS, BIG DATA AND TECHNOLOGY
has been found to be utilizing the model for making everything available for the customers
“under one roof”, which is actually a digital platform of the website for the company where
the user can buy, sell or even look through the products available for buying or selling.
The organization also provides so many business solutions, products and options to
the customers of the organizations that it may occur that the customers can become
overwhelmed with the products and services offered to them. The offers provided to the
customers are so huge in number that they automatically become rich in data. With such a
huge amount of data, it is often found that the data rich contents of the generated information
within the business becomes poor in the insights provided to the customers (Balachandran
and Prasad 2017). Amazon has thus implemented the best available combat format for the
gathered or generated business data. The organization has been trying to make the most of the
available information in the organization with the amalgamation of the available Big Data
Analytics technology to make sure that the organization is performing the best form of data
analytics informed decision-making procedure. The organization was not focusing on just the
Big Data Analytics Technique on making the informed business decisions but also the
enhancement of the recommendation engine as well (Atriwal et al. 2016). The enhancement
of the recommendation engine is for serving the customers only based upon the
overwhelming ideas that customers often face during the visiting of the websites for buying
or selling purposes.
Problem or potential of efficiency
The organization of Amazon Inc. has faced numerous problems since it has already
been found that the services and products that have been found to be provided to the
customers are keen on making the customers have the best services available but at the same
time they have been found to be overwhelming for the customers (Sorescu 2017). This is
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4DATA ANALYTICS, BIG DATA AND TECHNOLOGY
because there have been a huge incur of the business data and information with every aspect
of the potential expansion of the business. Since, the business of Amazon is found to be
serving various people all around the world in multiple nations, the number of customers is
found to be increasing at an exponential rate and at the same time it has been providing
multiple services to the customers as well. This is why, the business information has been
increased at such a rate that the business has been found to be overwhelming the customers
with the business systems.
This is the same reason that the organization wanted to implement the utility of the
business systems that would be feasibly handling the exponentially increasing amount of
business information within the organization. Without being able to manage the information
generated within the business, it would be difficult to handle the informative decisions to be
made to serve the customers. This is why it is important to manage or handle the business
information with the help of the Big Data Analytics. This is the same reason why the
organization of Amazon Inc. has been keen on using the analytics of Big data and fine-tune
their recommendation engine (Chawda and Thakur 2016). Amazon wanted a much more
analytical and informed idea about the customers which was only attainable given the
benefits of the Big Data Analytics. This is because; knowing a customer in the most detailed
way possibly helps the organization in predicting the buying or selling patterns of the
customers. Based on this information, Amazon would find it easier to recommend the
customers while they are either buying or selling products or accepting services from the
organization.
The problem that Amazon Inc. had been facing problems that was imbibed by the
exceeding amount of business information, but at the same time, the positive aspect of the
entire system was based on the willingness of the organization to take up the benefits of Big
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5DATA ANALYTICS, BIG DATA AND TECHNOLOGY
data Analytics for serving the customers with a much more informed suggestions while they
are on the website for buying or selling purposes.
Key metrics to define the problem
The technology that served as the key metrics for Amazon Inc. as the imbibed and
employed recommendation technology was excruciatingly based upon the collaborative
filtering technology. This is the combatting that Amazon required for the implementation of
the fine tuning required for the business information systems. The streamlining of the process
was extremely necessary because it was required to help the organization to make sure that
the customers had the best way possible to go through the website and implement the
persuasion that would be required in buying or selling of any item (Song et al. 2018). The
collaborative filtering technique was not available to the employees in the organization of
Amazon Inc., and this is why this was becoming an increasing problem to take care of the
requirements of the customers. The organization and the employees in charge of handling the
business data and customer information was facing a lot of problem with every expansion
that the organization had been making. The ways by which the problems can be identified is
the feedback of the customers as they share their experiences over the usability of the
websites and the overwhelming suggestions provided to them.
Methods to analyse the data generated in the organization
The data generated within the organization of Amazon Inc. required a special
treatment to help the business information to be generated and be organized to provide better
solutions to the problem (Marjanovic, Dinter and Ariyachandra 2017). The same reason is
required to help the organization with the informed decision making process by making the
organization be better aware about he buying and selling patterns of the customers and all the
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6DATA ANALYTICS, BIG DATA AND TECHNOLOGY
information generated within the organization about the things they are more likely to buy
and the things that they would be less likely to buy. Therefore, the most important
requirement of the customers would be to analyse all the intricate information regarding the
customers and their behaviour with the services and products.
Thus, the used technology for enhancing the recommendation filtering is based upon
the collaborative filtering technology which is dependent upon the perspectives and thinking
of the customers by building up the entire virtual picture of the customer (Marr 2015). The
business is more informed about the kind of person the customer is or the behaviour of the
customer based on the information patterns and behavioural website surfing patterns recorded
by the Big Data Analytics Techniques. This would be much useful for building up the
information about the customer himself or herself by building up an analytical virtual model
(Manogaran, Thota and Lopez 2018). This enables the organization in making up a much
informed and detailed idea about the customer and thus would further recommend a well-
informed buying or selling suggestion to the customers, even gathering information from the
similar profiles that have purchased or sold similar items.
Example of the inclusion of a dashboard
Data dashboards are important for providing the organization with a much more
precise objective of the analysis of performance metrics and establishes a much more
effective foundation for having an informed dialogue to be implemented. The dashboard
serves as an intelligence tool that business organizations put into use to make sure that the
data visualizations are displayed well enough to make the organization understand the
visualization of the analytics of the data in a much better way (Shmueli et al. 2017).
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7DATA ANALYTICS, BIG DATA AND TECHNOLOGY
The organization of Amazon Inc. uses the Lean Dashboards for this function which
makes the analysis and the visualization of the data analytics in a much more interactive
platform. This is because; the data that would be informed to be found out by the
organization for not just the purpose of enhancing the organization and its business
operations but for the primary reason of serving the customers with the best available
suggestions for the buying and selling of products through the website. Having interactive
data analysis would help in presenting recommendations to the customers in a much more
informed way.
Identification of the key stakeholders
The key stakeholders that would be involved in this case for finding out and
implementing the customers with a better-informed buying and selling suggestions can be
listed as follows:
The business executives
The board of directors
The people within the organization responsible for analysing the data (Akter et
al. 2017)
The decision-making bodies
The customers
Organizational benefits as per the analysis of the data
The benefits of the analysis of customer data to form a virtual image of the customer
as an individual would be much more beneficial to the organization of Amazon with not just
informed business decision making, but would also provide satisfaction to the customers as
they would find it essentially beneficial to be guided through the website with the best
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8DATA ANALYTICS, BIG DATA AND TECHNOLOGY
suggestions according to their buying or selling behaviours (Sun, Sun and Strang 2018). This
would make the customer feel much easier to surf through the websites and at the same time
this would not just help in retaining the customers but would also bring in new potential
customers on the basis of the information about the best available services spread through
word of mouth.
Factors that influence the decision-making process by data analysis
The decision-making process for Amazon Inc. is influenced by the idea and the
feedback of the customer to understand how the business has been overwhelming with
products and services (Jha, Jha and O'Brien 2016). Being nation-specific with the products
and services is also another aspect of the implementation.
Challenges in the implementation of the solution
The only challenge that can be found to be occurring during the implementation of the
solution are the management of the huge amount of data to understand all the implementation
of the analytics technique for the individual customers. It can also be found that the same
customers might have more than one account or more than one customer may have similar
buying or selling behaviour (Chen et al. 2016). These can often form challenges for Amazon
while implementing the system.
Reflection about the data analytics
According to the above report, the ways by which Amazon keeps on collecting the
business data for helping the users to navigate through the website, saves the time for the
users to browse through every available page of the website or the available mobile
application (Sun, Zou and Strang 2015). The external datasets can also help the retailers to
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9DATA ANALYTICS, BIG DATA AND TECHNOLOGY
gather the census data and have a better look at the demographic details. This would make the
customers extremely satisfied with the business services and help in retaining customers and
gathering the potential customer’s attraction as well.
Conclusion
Therefore, in conclusion, it can be said that the way by which the organization of
Amazon Inc. has been providing the organization with the best possible utilization of the Big
Data Analytics is solely based on the requirement of the business to serve the customer with a
better solution while they would be buying or selling any product or availing the services
available by Amazon Inc. The decision of utilizing the Big Data Analytics technique is
entirely based upon having a clear idea about the customers since they have been facing
challenges in handling the business information since they have been exponentially rising
given the multinational setting of the business. The services have made the customers be
more interested in the business but at the same time the organization have been facing trouble
handling the customers and their activities in the organization. The above report is thus based
upon how Amazon Inc. uses the Big Data Analytics technique to serve the customers in the
best way possible and also make sure that the business is being facilitated by it as well.
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10DATA ANALYTICS, BIG DATA AND TECHNOLOGY
References
Akter, S., Wamba, S.F., Gunasekaran, A., Dubey, R. and Childe, S.J., 2016. How to improve
firm performance using big data analytics capability and business strategy
alignment?. International Journal of Production Economics, 182, pp.113-131.
Atriwal, L., Nagar, P., Tayal, S. and Gupta, V., 2016. Business Intelligence Tools for Big
Data. Journal of Basic and Applied Engineering Research, 3(6), pp.505-509.
Balachandran, B.M. and Prasad, S., 2017. Challenges and benefits of deploying big data
analytics in the cloud for business intelligence. Procedia Computer Science, 112, pp.1112-
1122.
Barga, R., 2016, April. Processing big data in motion. In 2016 IEEE International
Conference on Cloud Engineering (IC2E)(pp. 171-171). IEEE.
Bell, P.C., 2015. Sustaining an analytics advantage. MIT Sloan Management Review, 56(3),
p.21.
Chawda, R.K. and Thakur, G., 2016, March. Big data and advanced analytics tools. In 2016
Symposium on Colossal Data Analysis and Networking (CDAN) (pp. 1-8). IEEE.
Chen, H.M., Schütz, R., Kazman, R. and Matthes, F., 2016, January. Amazon in the air:
Innovating with big data at Lufthansa. In 2016 49th Hawaii International Conference on
System Sciences (HICSS) (pp. 5096-5105). IEEE.
Jha, M., Jha, S. and O'Brien, L., 2016, June. Combining big data analytics with business
process using reengineering. In 2016 IEEE Tenth International Conference on Research
Challenges in Information Science (RCIS) (pp. 1-6). IEEE.
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11DATA ANALYTICS, BIG DATA AND TECHNOLOGY
Manogaran, G., Thota, C. and Lopez, D., 2018. Human-computer interaction with big data
analytics. In HCI challenges and privacy preservation in big data security (pp. 1-22). IGI
Global.
Marjanovic, O., Dinter, B. and Ariyachandra, T., 2017. Introduction to Organizational Issues
of Business Intelligence, Business Analytics and Big Data Minitrack.
Marr, B., 2015. Big Data: Using SMART big data, analytics and metrics to make better
decisions and improve performance. John Wiley & Sons.
Shmueli, G., Bruce, P.C., Yahav, I., Patel, N.R. and Lichtendahl Jr, K.C., 2017. Data mining
for business analytics: concepts, techniques, and applications in R. John Wiley & Sons.
Song, P., Zheng, C., Zhang, C. and Yu, X., 2018. Data analytics and firm performance: An
empirical study in an online B2C platform. Information & Management, 55(5), pp.633-642.
Sorescu, A., 2017. Data‐driven business model innovation. Journal of Product Innovation
Management, 34(5), pp.691-696.
Sun, Z., Sun, L. and Strang, K., 2018. Big data analytics services for enhancing business
intelligence. Journal of Computer Information Systems, 58(2), pp.162-169.
Sun, Z., Zou, H. and Strang, K., 2015, October. Big data analytics as a service for business
intelligence. In Conference on e-Business, e-Services and e-Society (pp. 200-211). Springer,
Cham.
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