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Analyze
the Gap between Theory and Practice in Business Intelligence
Technology has given a lot of boost
to the business world and things have been going great in so many ways. One
such contemporary concept is a business intelligence (BI). It is important to
understand what BI is before looking at its theory in relation to the practice.
Business Intelligence is a concept, which allows companies to use their data
and software to extract data in a way that it provides actionable and
considerable insights, which business organizations can use to make tactical
and strategic business decisions. It is a fact that data is becoming
increasingly important for organizations, and if things have to be managed
properly, then it is critical to use this available data
The theory and practice are two
concepts, which go in relation to each other, and if there is a theory, then
there must be its practical application as well. But issues start from the
point when the practice is different from theory. It is important to understand
that there can a lot of reasons for the gap between theory & practice, but
this gap is not good for any organization and industry. It means that when
there theory & practice is having any length of the gap, then people who
are implementing the theory are getting it wrong, and that’s why they are not
able to properly implement theories into practice. But good thing is that when a
proper analysis is done to evaluate the problem, then business organizations
can get an idea of why this gap is existing and what can be done to mitigate or
at least decrease this gap. In terms of BI, there are various theories and
concepts, which are used to complete the process of BI. One such theory for BI
is data mining, which is primarily used in the process of completing business
intelligence
It is vital to look at the elements
of data mining, and then looking at the gap between theory & practice for
data mining during the process of BI. This theory has been selected because the
process of BI cannot be completed without data mining, and it is one of the
most crucial aspects, which cannot be ignored. If data mining is not done
properly, then it is almost impossible for organizations to get any insights
from the concept of business intelligence. Once the data is collected, the next
step is to analyze and examine this available data, and this process is called
data mining. When big data is there for an organization, then they will have to
extract useful data, which can be used to get better insights, and if data
mining is not properly completed, then extracted data will not help to make
informed decisions. In simple terms, it can be said that data mining is a
technique, which gives a sense to data, which is spread without any sense or
meaning. The collected data is meaningless unless it is understood through data
mining to know about patterns of sales, revenues, customer choices, etc. There
are various unnoticed and important patterns in the available data, which
always went unnoticed because there was no technique to get insights, but with
the essence of data mining, organizations are able to do so
It is vital to look at different
research work to see how theory and practice of data mining are showing the
gap, and how this gap is increasing problems for the concept of business
intelligence. One study was conducted to look at data mining issues along with
opportunities. This study was conducted to increase the level of nursing
knowledge. The Healthcare field is one good example, who has taken a lot of
benefits from the essence of data mining and business intelligence, because a
lot of useful data is available for them, and if this data is used properly, it
helps to show various valuable patterns. For instance, nurses are involved in a
variety of tasks, but nursing knowledge has been limited, which shows that a
lot of opportunities are there in this regard. The senior and expert nurses'
way of handling patients is far more effective as compared to young and
inexperienced nurses, and if health care facilities can keep this data together
of senior nurses, then it can come up with great insights for the young nurses
to learn a lot. Data mining is a great tool to extract data for the nursing
knowledge, and then using it for knowing the trends, patterns, and methods of
dealing with a variety of patients. In this research, a case study was analyzed
to see how clinical data can be useful with regards to nursing interventions,
and how their conduct is benefiting patients with better outcomes. It was concluded
that healthcare systems should make arrangements to collect and analyze data of
expert nurses, and then it is used with the help of data mining technique so
that better health care systems are developed with the passage of time
It is quite important to keep in
mind that data mining when used as a business intelligence theory, can be
useful in so many ways, but its application as per theory is critical. If there
will be a gap between the two, then outcomes will not be achieved as per
expectations. For instance, if a super retail store is trying to see patterns
of customer purchase, then it will have to use business intelligence in light
of data mining to get useful insights. For instance, there may be a trend,
where one product is purchased from the customers in relation to the other
product, like a customer purchasing baby diapers may also look to purchase
other utility items used for kids at home. Now, the retail store will have to extract
and analyze data with the help of data mining to get the results and patterns
and see if there is any correlation between the two. If the trend shows that
baby products are also purchases by people, who purchased baby diapers, then it
is important for managers to make a decision on how both product categories
should be placed in the store so that customers may purchase both items
After looking at different elements
of business intelligence with its theory and practice, it can be said that if
theory and practice will have gaps, then a theory cannot be effectively
utilized. So, this gap should be minimized as much as possible. Otherwise, the
organizations cannot get better insights, which are needed to make great and
informed decisions. Business intelligence has proved extremely beneficial for
organizations, and if they can use it properly, it can be instrumental for both
short term and long term perspective. It was also found that data mining theory
had gaps with its practical application, but if it is used properly, it can
provide valuable information to make strategic decisions, which can reward
organizations with great results.
References of Analyze the Gap between Theory and Practice in Business Intelligence
Goodwin, L., VanDyne, M., Lin, S., & Talbert, S.
(2003). Data mining issues and opportunities for building nursing knowledge. Journal
of Biomedical Informatics, 36(4/5).
Hatasa, Y. A. (2013). The Gap between Theory and
Practice: Problems and Possibilities. Journal CAJLE, 14, 1-17.
Kong, D., Zhou, Y., Liu, Y., & Xue, L. (2017).
Using the data mining method to assess the innovation gap: A case of
industrial robotics in a catching-up country. Technological Forecasting
and Social Change, 119, 80-97.
Li , A., & Zhang , L. (2009). A Study of the Gap
from Data Mining to its Application with Cases. 2009 International
Conference on Business Intelligence and Financial Engineering. IEEE.
Pratt, M. K., & Fruhlinger, J. (2019). What
is business intelligence? Transforming data into business insights.
Retrieved April 10, 2020, from
https://www.cio.com/article/2439504/business-intelligence-definition-and-solutions.html
Rana, S. (2018). Covering the Gap between Theories
and Practices in Business and Management. FIIB Business Review, 7(2).
Richards, G., Yeoh, W., Chong , Y. L., & Popovič, A. (2019). Business Intelligence Effectiveness and Corporate Performance Management: An Empirical Analysis. Journal of Computer Information Systems, 59(2), 188-196.
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