Analyzing Big Data Integration's Impact on Walmart's Decision Making

This report provides a comprehensive analysis of Walmart's integration of big data, exploring its impact on decision-making processes and return on investment (ROI). The study examines how Walmart utilizes big data from various sources, including web browsing, social media, and customer transactions, to gain insights into consumer behavior, market trends, and operational efficiencies. The report highlights the benefits of predictive analytics, improved inventory management, and enhanced customer engagement resulting from Walmart's data-driven strategies. It also addresses challenges such as the cost of advanced technologies, the need for skilled professionals, and the limitations of historical data. The report evaluates Walmart's successes and failures in adopting big data, concluding that big data analytics is a crucial tool for improving profitability and making sound business decisions, particularly in the retail sector. The report references various academic sources to support its findings.

BIG FINANCIAL DATA
FUNDAMENTALS

Table of Contents
INTRODUCTION...........................................................................................................................1
MAIN BODY...................................................................................................................................1
Task 1.....................................................................................................................................1
Task 2.....................................................................................................................................3
Task 3.....................................................................................................................................4
CONCLUSION................................................................................................................................5
REFERENCES................................................................................................................................6

INTRODUCTION
Most of the big organisations collect large amount of data from web browsing and other
social networking sites. All these data are being used to identify insight detail about the firm and
pattern of working practices (Wamba and et.al., 2015). Big data integration supports business in
gaining high return over their investment. It supports entities in making sound business
decisions. Present study is based on Walmart, it is the multinational retail firm. It has more than
11718 stores in 28 countries. Current report will critically discuss impact of big data integration
on decision making of firms. Furthermore, it will evaluate the success and failure aspects of big
data adoption by enterprises. Moreover, study will explain effectiveness of investing in big data
analytics in order to get high return over investment.
MAIN BODY
Task 1
As per the view of Crompton, (2016) big data can be considered as large data set. These
unstructured data are analysed by companies in real time. That supports entities in discovering
new opportunities that are hidden temporarily. Big sized companies are taking support of big
data integration techniques. Entities use advance technologies in order to analyse large size data.
This data involves images, videos, transaction data, email, social media integrations etc. When
all these details are being combined and analysed by using technologies, then companies get new
ideas and opportunities that support the firm in making sound decisions.
Lam and et.al., (2017) argued that collecting and managing data is not the difficult task
for companies. But analyses and extraction of information is the major challenge for entities.
Analyses of big data supports in measuring volume, velocity, variety and values of the
organisation. That assists business unit in finding new ways which can help the firm in gaining
success. Decision making process is the most important part of corporation and correct decisions
support entities in minimising strengths and strengthening strong point (Erl, Khattak and Buhler,
2016).
According to Baesens and et.al., (2016) it is very important for the organisation to have
good knowledge about customers, market conditions, trends etc. These details support entities in
modifying their operations in right direction so that effective decisions can be made by
companies for successful future. It assists in making smarter decision, future judgements that
can make the firm unique or different from other competitors. In order to enhance decision
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making effectiveness, entities are combining unstructured data from email, images, social
communication etc. All these details are being analysed in an accurate manner that aids in
making sound business decisions. One of the great model that is applied by Walmart is predictive
analytics technique. This is beneficial tool that assists in utilising big data effectively and
bringing innovation in the business unit. This application has helped Walmart in making
necessary changes in its strategies that have given success to the entity and now, it has become
the market leader in the field of retail.
Shim and et.al., (2015) stated that integration of big data is the beneficial tool and assist
in identifying loop fall in the operations. That helps the management in making changes in
operational process so that entity can gain competitive advantage. Big data integration is helpful
mechanism that assists entities in making critical business decisions. Apart from this, it aids in
increasing business performance and making sound investment decisions so that entity can
generate more return over their investments. In the big data analytics entity take support of social
media chats, email messages, images, videos etc. that supports in identifying market trends. This
real data supports the firm in enhancing engagement of consumers and retaining them in the
organisation for longer duration. This data set makes the firms aware with the needs of
consumers. For example Walmart uses big data in order to identify requirements of consumers
and accordingly it designs its loyalty programs. 90% sales have been increased by using these
big data, this has helped the firm in earning more revenues and becoming the global leader.
As per the view of Bates and et.al., (2014) big data integration is the beneficial tool but
managing such unstructured information is the difficult task. Management has to spend much
time and in the absence of expertise, entity may fail to take sound business decision. Sometimes,
it may create confusion that may affect overall profitability of the entity to great extent. Use of
advance technologies in order to analyses these big data is costly task and time consuming
activity. That is why, small firms are unable to make sound decision by using this method. Mall-
Mart is applying this methodology effectively and taking advantage of this integration. Walmart
is the firm that have more than 245 million consumers and having more than 10900 stores. It has
10 active websites across the world. Cited firm is actively present on online activities and that
has made it the world’s largest retailer. Walmart data analytical culture supports the firm in
improving customer emotional intelligence. This has helped the cited firm in increasing its online
selling by 15%. In the year 2012, Walmart has made experiment to move from 10 node hadoop
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to 250 node hadoop clusters. This has supported entity in making sound decision and improving
its online services. Now, e-commerce technologies of Walmart are able to deliver quality
services to the customers.
Task 2
As per the view of Minelli, Chambers and Dhiraj, (2014) big data integration is the
beneficial tool that assists business units in identifying needs of consumers. Companies collect
information of consumers through email, social media etc. and try to identify their buying
behaviour. It supports the firms in making necessary changes in their current product and
services so that entity can provide satisfactory services to consumers and can gain attention of
mass audience. Predictive analyses method is the beneficial technique that aids in developing
unique brand image and gaining competitive advantage. With the assistance of big data,
company can easily look at the suppliers, consumers and stakeholders and can make sound
decisions that can reduce risk of business.
Mayer-Schönberger and Cukier, (2014) argued that integration of big data is costly task
because entity is required to invest in enhancing its computer powers. There is required to have
hadoop so that real time analyses can be done. This hadoop is very important in order to do real
time analyses. One of the main issues in big data integration is that companies have to use
different case studies and on the basis of this, they can make their decisions. Sometimes, it gives
negative results to the business units.
On other hand, Hurwitz, Kaufman and Bowles, (2015) stated that big data integration is
advantage for the companies. As it helps in understanding sales trends and get to know about
exact working practices for improvement. This helps in making sound decisions so that errors
can be minimized and cited firm can improve its profitability. Walmart has get benefited from
big data analyses, this has supported cited firm in targeting potential buyers. Walmart has
gathered detail about buying behaviour of consumers, their income source and financial
capabilities by using Facebook, Twitter and other social networking application. After that, it has
made changes in its online services that has given benefit to the entity and enhanced its online
sales by 15% in the year 2014. This has given amazing shopping experiences of all consumers
and enhances their satisfaction level.
One of the main benefit of using predictive analyses of big data is that it has helped the
firm in managing its inventory. By this way, cited firm become able to reduce its cost to great
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extent. It has supported in improving its supply chain management thus, it became able to reduce
its overstock issues (The Advantages and Disadvantages Of Real-Time Big Data Analytics,
2017). Walmart has suggested to their suppliers to take support of real time vendor inventory
management system so that production of products that are not in demand can be minimized. Big
data analytics has improved store checkout process for consumers in the organisation. On other
hand, big data analyses can be done by experts only. But due to having big data skills crises cited
firm has issues in managing its operations well. Cited firm has limited time to find professionals
because if it takes huge time then competitors will influence the mind of consumers (Five ways
Walmart uses big data, 2017). Another issue in big data analyses for Walmart is prediction.
There are limited historical data present and it is very difficult for the management to make
correct prediction by using small sample. In festival seasons, needs of consumers get changed
thus, it is very hard to identify the strategic decision of consumers.
Task 3
As per the view of Wamba and et.al., (2015) big data integration is the beneficial tool that
helps the companies in understanding consumers buying behaviour and market trends. By using
historical data, companies make sound decisions so that these can grow well. Use of big data
supports the firms in gaining high return over their investment and enhancing their profitability
to great extent. Traditional data processing techniques were unable to give accurate details about
the patterns, trends (37 Big Data Case Studies with Big Results, 2018). Thus, entities were not
able to manage their operations well and making changes in business units. 91% of market
leaders believe that use of big data supports the firm in making sound business decisions. That
assists in gaining high return over their investments. For example, DELTA is the firm which has
provided facility of tracking their bags and mobile devices. This application was downloaded by
many consumers that have enhanced sales of the firm and it became able to get high return over
its investments.
Walmart is the global leader, it has adequate financial resources. This helps the firm in
making investment in order to improve its profitability. Walmart has invested huge amount in
improving its computer powers. Hadoop and NOSQL technologies are highly expensive and this
has increased cost of the entity (How Big Data Analysis helped increase Walmarts Sales
turnover?, 2015). But use of big data analyses has supported the firm in identifying buying
behaviour of the consumers. That has helped the firm in raising its online sales by 15%. Thus, it
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became able to gain high return over its investments. Walmart has used this application very
well that has resulted in enhancing its sales volume. Its incremental revenues have been
increased by 1 billion. Cited firm has made changes in its e-commerce strategy that has
supported in increasing its profitability to great extent (The Advantages and Disadvantages Of
Real-Time Big Data Analytics, 2017). Entity has invested huge amount in improving hadoop
from 10 to 250. But this has given amazing experience to the clients, now consumers are able to
get e-receipt of their purchase. Hadoop is able to manage 1000 Walmart stores globally that
gives detail about exact location of any store. New shipping policy has supported in improving
its sales volume, now free shipping has been increased by 5% within one year (Baesens and et.al,
2016).
Big size organisation should use big data analyses in an effective manner. They have to
combine historical data effectively and have to manage these details significantly. Improvement
in Hadoop is the best strategy of managing data and making sound business decisions.
Combining customer transactions and proper interaction can help the firms in predicting the
loophole in current practices so that entity can make necessary changes in the workplace that can
give amazing experiences to the consumers and can enhance their satisfaction level (How Big
Data Analysis helped increase Walmarts Sales turnover?, 2015). By this way, organisation
would be able to get high return over their investments.
CONCLUSION
From the above study, it can be concluded that big data analyses is the best way to
improve profitability and ROI of business unit. Use of big data assists in making sound business
decisions. This is the way that aids firms in doing real time analyses so that strategy of
competitors can be identified and the company can make its strategy that can support in making
the firm one step ahead from competitors.
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REFERENCES
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Baesens, B. and et.al., 2016. Transformational issues of big data and analytics in networked
business. MIS quarterly. 40(4).
Bates, D. W. and et.al.,2014. Big data in health care: using analytics to identify and manage
high-risk and high-cost patients. Health Affairs. 33(7). pp.1123-1131.
Crompton, J., 2016, September. How can we turn intelligent energy into profitable operations?.
In SPE Intelligent Energy International Conference and Exhibition. Society of Petroleum
Engineers.
Erl, T., Khattak, W. and Buhler, P., 2016. Big Data Fundamentals. PRENTICE HALL, available
at: file:///C:/2016-2017/Research/Paper/COR_Jimmy and Vir/References/Referencing for
Li/37. pdf.
Hurwitz, J., Kaufman, M. and Bowles, A., 2015. Cognitive computing and big data analytics.
John Wiley & Sons.
Lam, S. K. and et.al., 2017. Leveraging frontline employees’ small data and firm-level big data
in frontline management: An absorptive capacity perspective. Journal of Service Research.
20(1). pp.12-28.
Mayer-Schönberger, V. and Cukier, K., 2014. Learning with big data: The future of education.
Houghton Mifflin Harcourt.
Minelli, M., Chambers, M. and Dhiraj, A., 2014. Conclusion.Big Data, Big Analytics: Emerging
Business Intelligence and Analytic Trends for Today's Businesses. pp.169-174.
Shim, J. P. and et.al., 2015. Big Data and Analytics: Issues, Solutions, and ROI. CAIS. 37. pp.39.
Wamba, S. F. and et.al., 2015. How ‘big data’can make big impact: Findings from a systematic
review and a longitudinal case study. International Journal of Production Economics. 165.
pp.234-246.
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37 Big Data Case Studies with Big Results. 2018. [Online]. Available through:
<https://www.businessesgrow.com/2016/12/06/big-data-case-studies/>.
Five ways Walmart uses big data. 2017. [Online]. Available through:
<https://www.chainstoreage.com/article/five-ways-walmart-uses-big-data/>.
How Big Data Analysis helped increase Walmarts Sales turnover?. 2015. [Online]. Available
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The Advantages and Disadvantages Of Real-Time Big Data Analytics. 2017. [Online]. Available
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