MIS609 Data Management and Analytics: Amazon Case Study Analysis

This case study report analyzes Amazon's data management and analytics practices, focusing on how the company utilizes big data, cloud computing, and predictive analysis to make informed decisions and improve its business operations. The report begins with an introduction to Amazon's business and its reliance on data analytics, followed by an overview of key data analysis concepts such as big data, cloud computing, graphical frameworks, and predictive analysis. It then explores the various data sources used for collecting assignment information, including primary, secondary, and tertiary sources. The analysis section delves into the problems Amazon faces in handling unstructured and structured data, the implementation of data analysis concepts across different stages of its operations, and the challenges encountered during the implementation of big data analytics (BDA) technology, such as employee skill gaps and data privacy concerns. The report highlights the benefits of implementing BDA, including increased revenue, improved customer satisfaction, and optimized business processes. The case study concludes with findings and recommendations to improve Amazon's data analytics strategies and overall performance. The report is a contribution to Desklib, a platform offering students access to AI-powered study tools and past assignments.

MIS609 Data Management and Analytics
MIS609 Data Management and Analytics
Assessment 2
Case Study Report: Data Analytics for Organisational Decision-Making
Individual Report
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Student Name:
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MIS609 Data Management and Analytics
Table of Contents
Introduction......................................................................................................................................2
Section 1: Introduction of Selected Business Enterprise.................................................................2
Section 2: Introduction to Data Analysis Concepts.........................................................................3
2.1 Big Data.................................................................................................................................3
2.2 Cloud Computing...................................................................................................................3
2.3 Graphical Framework............................................................................................................4
2.4 Predictive Analysis Approach...............................................................................................4
Section 3: Data Sources for Collecting Assignment information....................................................4
Section 4: Analysis..........................................................................................................................5
4.1 Problems faced via Amazon..................................................................................................5
4.2 Implementation of data analysis concepts by Amazon..........................................................6
4.3 Issues faced by Amazon while implementing data analytics................................................6
4.4 Benefits of implementation of new change in Amazon.........................................................7
Section 5: Conclusion, Findings, and Recommendations...............................................................8
References........................................................................................................................................9
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MIS609 Data Management and Analytics
Introduction
Data management & analytics refers to the managerial procedure that includes collection,
storage, validation, & processing of the organizational data in order for ensuring regarding the
accessibility, timeliness, and reliability of users’ data. For every business enterprise, using
effective data management technology is very important because data is produced and consumed
in a very unprecedented manner. This document is demonstrating the understanding and
knowledge of a broad scenario of data management & analytics to resolve the company’s real
issues. Data analytics concepts are also illustrated that are used by companies. Data resources are
also listed in the report to analyse data analytics-related problems. Some suggestions are also
given to eliminate issues that are faced by enterprises.
Section 1: Introduction of Selected Business Enterprise
Amazon is a US-based online retailing enterprise and its headquarters are situated in Seattle,
Washington, U.S. The enterprise was founded in 1994 by Jeff Bezos as an online bookseller.
Then, it had expanded its business and now it is selling everything from trustable brands such as
grocery products, electronic products, digital services, and so on (Neate, 2021, Para 1). Now, it is
operating its e-commerce services worldwide (US, Australia, India, and so on) under different
brands. 1,335,000 people are employed via Amazon.
Amazon is selected for case scenario-based data analysis and management because it is using
real-time and up-to-date data analytics for making effective decisions. Huge information related
to Amazon is available that is used for data analytics activities to handle organisational issues
effectively. It uses a data analytics approach to track and fulfill its customer’s needs and amplify
its financial performance (Amazon, 2020, Para. 1-2). Amazon’s typical business is to deal in
grocery products, consumer electronic products, beauty products, merchandise products, gourmet
food products, personal-care & health items, kitchen items, baby products, and so on. It is
considered as biggest e-commerce retailing enterprise in Australia.
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MIS609 Data Management and Analytics
Section 2: Introduction to Data Analysis Concepts
Data gathering, storing, analyzing, and management is very important operations of data
analytics that are needed to extract essential information of Amazon. Data effective classification
enables the procedure of data prediction and detection that has a huge influence on the decision-
making process of the enterprise. To become successful in the online retailing market, it is
needed that Amazon must understand their customer’s purchasing behaviour to optimize the
company’s performance and create suitable competitive benefits for a company. Amazon uses
data analysis concepts to amplify understanding of operational requirements and present & future
strategic needs by considering the preferences and interests of stakeholders.
2.1 Big Data
Amazon enterprise gathers big-data from their online consumers and applies the data-predictive
analytics to know purchasing behaviour of their customers & modernize the delivery process of
required services or products to their consumers. The collaborative (filtering-oriented)
suggestion technique is also used by Amazon to offer products and services that are looked at by
consumers. To deliver effective services and products to consumers & boost the enterprise’s
sales, Amazon has launched 360 degree views of consumers to market the company’s products
on the basis of big data. CFE (collaborative filtering-oriented engine) is helping Amazon to
analyse details of consumers such as what type of items they are searching for, what type of
products they have viewed, what type of products they have purchased, and so on. Then, this
analytics data is used to recommend the products and services to online consumers on the basis
of their purchasing behaviour.
2.2 Cloud Computing
Cloud-computing services (AWS (Amazon Web Service)) were presented by Amazon in 2006 to
secure the enterprise’s big data application & amplify their scalabilities. Amazon uses cloud
computing-based techniques in the different big data applications such as suggestion engine,
fraud detection, IoT (Internet of things) processing, data warehousing, clickstream analytics, and
so on (Marr, 2020, Para. 2).
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MIS609 Data Management and Analytics
2.3 Graphical Framework
Through tracking the company’s inventory, Amazon enhances its supply-chain and Amazon
utilizes big data analytics techniques for selecting closed warehouses from shipping addresses of
consumers. The graphical framework is used by Amazon for knowing best scheduling for
shipping route & delivery (Ullah & Noor-E-Alam, 2018, P. 23).
2.4 Predictive Analysis Approach
Amazon applies ML (machine learning) technology, statistical algorithm, & AI (Artificial
intelligence) technology to collect the data that is used for analysing the customer’s buying
behaviour. To enhance the effectiveness of marketing, predictive analysis has helped Amazon to
reach a large volume of competitors’ consumers and diverse individuals & enhance the
consumer’s retaining (Sun, Sun, & Strang, 2018, P. 162-169).
The collected information is converted into company visions that are used by Amazon for
making effective decisions and implementing these decisions into actions that will help to
improve the company's services. Amazon collects real-time information with the help of big
data, AI, MI, cloud computing, and other various data analytics technologies and it helps
Amazon to execute data analysis activities and produces effective results to improve the
company’s performance and selling.
Section 3: Data Sources for Collecting Assignment information
In general, different kinds of data or information resources are available that are used to gather
the data analytics-related information and these resources are tertiary, primary, and secondary
such as journals, articles, & online websites. These resources are very essential to understand
regarding each kind of information or material source & this is also vital for knowing which kind
of data is appropriate and perfect for this research work, data searching & gathering (Huang, et
al. 2020, P. 690-700). For this Amazon case study, the qualitative data analytics methodology
has been utilized and it will utilize secondary kinds of data sources for collecting the material
regarding the data analytics approach. Various online sources are also employed for the
collection of material of Amazon. These sources are very helpful for enhancing the knowledge
about the different data analytics tools including big data technology. The book’s materials have
also been considered in this assignment to optimize knowledge about big data analysis tools.
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MIS609 Data Management and Analytics
Different online web pages, recent published article, literatures, and journal have also been used
to collect information that is showing the data analytics’ usage in the working process of
Amazon enterprise. The materials that are used in this assignment report have detailed
information about the current data analytics problems of Amazon with information analytics
technologies that would be used by Amazon to improve the company services (Kaushik, et al.
2018, P. 21-31).
The purpose of this data source section is to analyse the problems of Amazon and data or
information analytics technology that is used through Amazon. During the material’s gathering,
the trustworthiness of materials is also maintained. Thus, these data sources would be helpful to
Amazon for taking effective decisions within the company to enhance company services
(Shahbaz et al., 2020, P. 3).
Section 4: Analysis
4.1 Problems faced via Amazon
Problems that are faced by Amazon in BDA (big data analytic) are generated from the handling
of unstructured & structured organisational information. The unstructured information contains
data information such as comments, feedback, tweets, reviews, voices, likes, links, and so on.
The structured information contains data information such as name, shipping address, contact
details, preferences, gender, DOB, & other details about the online consumers. It isn’t possible
for Amazon for ensuring that the big-data analytics approach is completely clean & free from
any error. Information of suggestion engine is totally dependent on the data analytics and data
management to enhance the selling of Amazon enterprise. Due to this, Amazon is facing
problems to manage a huge amount of data because it is enhancing the complexity to integrate
big data information that is collected from the various resources and formats (Hillion, 2018,
Para. 2-3). It may be possible for Amazon that big data’s usage can amplify the satisfaction level
and retention of consumers and optimize company processes but it would create challenges or
problems for Amazon to generate effective business values throughout the business.
Thus, a major issue that is faced by Amazon is managing a huge amount of company data and
due to this, storage, process, & analysis of gathered information isn’t easier as information’s size
is too large and it is gathered from various sources and into various formats. A conventional data
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MIS609 Data Management and Analytics
management approach that is employed by Amazon is a simple data management system but this
can’t be efficient for doing depth analysis of gathered data information to make an effective
prediction about the buying behaviour of consumers. Thus, Amazon is currently facing the
problem to meet the needs of their consumers due to the company's unsuccessful database
management (Mariani & Wamba, 2020, P. 339-350). So, it is needed that amazon must use the
effective consumer behaviour tracking data analytics tool and analyse their requirements to meet
their demands for improving their satisfaction level
4.2 Implementation of data analysis concepts by Amazon
Amazon executes various data analytics concepts to improve the effectiveness of business
processes and operative functionalities. Amazon is implementing data analytics concepts in
different stages such as the initiation stage, planning stage, & implementation stage. In the first
initiation stage, information is gathered to know the needs of online consumers, the gathered
information is analyzed to understand the buying requirements of consumers (Akter & Wamba,
2016, P. 174-192). After that technology-related needs will be recognized and then, data related
with the usage of various data analytics related will also be achieved.
In the second planning stage, standards for data analytics quality, success, and closure will also
be estimated. Then, timeline, costing, and scope will also be set and then, stakeholders’ needs are
also known. After that planning will be done to perform data analytics activities in the business
operations of Amazon. Lastly, in the implementation stage, the designed plans of the second
stage will be executed and data analysis will be achieved to know customer’s needs according to
the planning, then a data analytics report will be produced. Thus, utilization of the big-data
concept is helpful for Amazon to offer personalised products and services, set dynamic prices of
products, optimize supply chain system, predict the buying behaviour of consumers, improve
consumer services, improve detect frauds and customer security.
4.3 Issues faced by Amazon while implementing data analytics
During the implementation of new modifications of BDA technology, Amazon can face various
problems such as:
1. Lack of working abilities of company workers can enhance their issues in the utilization
of BDA technology. Workers will feel uncertainty during the usage of big-data because
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MIS609 Data Management and Analytics
they have no sufficient knowledge about big data. Hence, it will enhance the problem of
employee turnover-rate.
2. Illegitimate access of big data can impact the consumer’s privacy. Therefore, it is needed
that Amazon must use employee security technology to protect customers’ anonymity
and manage their privacy (Arunachalam, Kumar, & Kawalek, 2018, P. 418-422).
4.4 Benefits of implementation of new change in Amazon
Execution of BDA technology will help Amazon to make decisions and amplify the company’s
revenue growth. New modification in data-driven areas produces non-tangible and tangible
business values for Amazon such as enhancing strategic business’s understanding and improving
the company’s productivity. The use of BDA concepts in Amazon's business operations has
enhanced its sale via 45%. BDA has improved customer’s satisfaction and retention and business
procedures (Raguseo, 2018.P. 190-191). Predictive analytics, cloud computing, BDA, graph
theories for supply-chain management, & other data analytics technology will help Amazon to
improve the company’s decision-making. Thus, it will enhance correctness in estimating
customers’ buying behaviour to meet their needs and gain company growth.
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MIS609 Data Management and Analytics
Section 5: Conclusion, Findings, and Recommendations
It has been concluded that BDA is offering different benefits to Amazon such as enhancing
strategic business’s understanding and improving the company’s productivity, enhancing selling,
decision-making, and business procedure of enterprise. Different kinds of data or information
resources have been used to gather the data analytics-related information and these resources are
tertiary, primary, and secondary such as journals, articles, & online websites. Amazon has faced
a major issue i.e. managing a huge amount of company data and due to this, they have failed to
meet consumers’ needs. BDA has produced non-tangible and tangible business values for
Amazon such as enhancing strategic business’s understanding and improving the company’s
productivity. It has been found that this study has helped to optimize the marketing and business
operations of Amazon.
There are some recommendations for Amazon that they must feel comfortable to employees
about the utilization of BDA approaches. For that purpose, Amazon can provide required
training to the company’s employees to increase their adopting capabilities of BDA technology.
Thus, big data’s understanding can be enhanced in-front of workers by showing working,
abilities, and other features of BDA by visualization reports and dashboard system. Amazon
should enhance the privacy and security of data-driven approach by applying face-recognition
techniques that will help them to protect customer secrecy and maintain the BDA approach’s
access-control security.
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References
Akter, S., & Wamba, S. F. (2016). Big data analytics in E-commerce: a systematic review and
agenda for future research. Electronic Markets, 26(2), 173-194.
https://dx.doi.org/10.1007/s12525-016-0219-0
Amazon, (2020). About Amazon. [Online] Retrieved from: https://www.aboutamazon.com/
Arunachalam, D., Kumar, N., & Kawalek, J. P. (2018). Understanding big data analytics
capabilities in supply chain management: Unravelling the issues, challenges and
implications for practice. Transportation Research Part E: Logistics and Transportation
Review, 114, 416-436. https://dx.doi.org/10.1016/j.tre.2017.04.001
Hillion, S. (2018). A culture of Analytics: Why Amazon & Netflix Succeed While Other Fail.
TIBCO. Retrieved from: https://www.tibco.com/blog/2018/06/27/a-culture-of-analytics-
why-amazon-netflix-succeed-while-others-fail/
Huang, Y., Liu, H., Li, W., Wang, Z., Hu, X., & Wang, W. (2020). Lifestyles in Amazon:
Evidence from online reviews enhanced recommender system. International Journal of
Market Research, 62(6), 689-706.
Kaushik, K., Mishra, R., Rana, N. P., & Dwivedi, Y. K. (2018). Exploring reviews and review
sequences on e-commerce platform: A study of helpful reviews on Amazon. in. Journal
of Retailing and Consumer Services, 45, 21-32.
Mariani, M. M., & Wamba, S. F. (2020). Exploring how consumer goods companies innovate in
the digital age: The role of big data analytics companies. Journal of Business
Research, 121, 338-352. https://dx.doi.org/10.1016/j.jbusres.2020.09.012
Marr, B. (2020). Amazon: Using big data to understand customers. Bernard Marr & Co.
Retrieved from: https://www.bernardmarr.com/default.asp?contentID=712
Neate, S. (2021). Amazon Australia: Everything you need to know | finder.com.au. Retrieved
from https://www.finder.com.au/amazon-australia
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Raguseo, E. (2018). Big data technologies: An empirical investigation on their adoption, benefits
and risks for companies. International Journal of Information Management, 38(1), 187-
195. https://dx.doi.org/10.1016/j.ijinfomgt.2017.07.008
Shahbaz, M., Gao, C., Zhai, L., Shahzad, F., Abbas, A., & Zahid, R. (2020). Investigating the
Impact of Big Data Analytics on Perceived Sales Performance: The Mediating Role of
Customer Relationship Management Capabilities. Complexity, 2020, 1-17.
10.1155/2020/5186870
Sun, Z., Sun, L., & Strang, K. (2018). Big data analytics services for enhancing business
intelligence. Journal of Computer Information Systems, 58(2), 162-169.
https://doi.org/10.1080/08874417.2016.1220239
Ullah, A. S., & Noor-E-Alam, M. (2018). Big data driven graphical information based fuzzy
multi criteria decision making. Applied Soft Computing, 63, 23-38.
10.1016/j.asoc.2017.11.026
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