Business Intelligence: Analyzing the Gap Between Theory and Practice

This report provides a comprehensive analysis of the gap between business intelligence (BI) theory and its practical application. It begins by outlining common BI theories, including data integration, real-time analytics, and collaboration and teamwork. The evolution of these theories is then discussed, highlighting advancements in techniques and approaches. The report explores the practical applications of these concepts, using examples like banking organizations and e-commerce websites. A significant portion of the report is dedicated to a gap analysis of collaboration and teamwork, identifying the discrepancies between theoretical ideals and real-world implementation. The analysis explores the reasons behind this gap, such as a lack of business context and pressure on BI teams. The report concludes by examining the negative impacts of this gap on decision-making processes, affecting organizations, customers, and vendors. The report references several scholarly articles to support its findings and analysis.

Running head: Gap Between Theory and Practice in Business Intelligence
Gap Between Theory and Practice in Business Intelligence
Name of the Student
Name of the University
Author Note

1
Gap Between Theory and Practice in Business Intelligence
Table of Contents
Common theories in business intelligence or BI:......................................................................2
Evolution of the theories:...........................................................................................................3
Practical applications of the concepts:.......................................................................................3
Gap analysis of Collaboration and Teamwork:..........................................................................4
1. Explanation of the reason why the theory has been chosen:..............................................4
2. Analysis of the gap between theory and practice...............................................................4
3. The root cause of this gap..................................................................................................4
4. The effect of the gap..........................................................................................................5
References:.................................................................................................................................7

2
Gap Between Theory and Practice in Business Intelligence
Common theories in business intelligence or BI:
In accordance with the journal article “Business Intelligence Technology, Applications,
and Trends” by Obeidat et al. (2015) and several other scholarly articles explored in this
context, several common theories in business intelligence or BI has been discovered that are
important for theoretical as well as application aspect of business intelligence. In the
following sections each of these theories have been discussed in details.
 Data integration: data integration is the concept of combining data from different
resources. It basically combines the new data with the existing data. Business that
considers data collection in a regular basis for having better insight about the market
and the customer, needs a proper mechanism for data integration (Jaklič, Grublješič &
Popovič 2018). As business needs to collect information from various resources,
different database that belong to various server, data integration becomes various
important. If the new data is not properly integrated with the older data, it not only
affects the decision making process, the decision are less effective too. Hence data
integration is an important concept of business intelligence or BI. Data integration has
become more important in recent era due to variety of data sources. As data sources
has become diverse, there has been a demand for better data integration. Hence data
integration need to be properly executed with advance tools and techniques for
increased productivity and efficiency.
 Real-Time Analytics: another important concept of business intelligent system is
real-time data analytics. It basically means to analyze data in real time as soon as it is
available to the system. Data is collected through access to operational systems
(Koch, 2015). However sometimes business related transaction is fed to data
warehouse that is capable of analyzing data in real time and hence effective for real
time analytics.

3
Gap Between Theory and Practice in Business Intelligence
 Collaboration and Teamwork: it is another important concept and has been
regarded by many researchers in the selected articles that have been considered in this
context. Collaboration in the context of BI means integration of several collaborative
tool with business related software. It is aimed at improving data based decision
making process.
Team works refers to contribution of teams in decision making process through
effective application of collaborative business intelligence (Vogel et al., 2017). It is
aimed at bringing more efficiency and productivity in the decision making process as
the process for most of the organizations is still very complex to implement and
manage for business context as well.
Evolution of the theories:
 The data integration technique has evolved a lot in terms of technique and approach to
implementation. Previous version of data integration was based on Extract,
Transform, and Load (ETL), and reporting while the modern techniques are based on
data exploration and visualization. The motivation behind this innovation was to
allow more and more data to be integrated effectively due to increase in size and
volume of data (Larson & Chang 2016).
 Although BI supports real time analytics on data, the process was not as effective as
the data has significantly increased a lot both in terms of value and volume. Big data
and cloud computing has been integrated to provide more robust analysis of data both
in structured and non-structured form (Jaklič, Grublješič & Popovič 2018).
Practical applications of the concepts:
 Data integration is used for several commercial application. For example a banking
organization need to collect data across various sectors. It includes data of various

4
Gap Between Theory and Practice in Business Intelligence
categories like finance, banking, customer relationship and several other categories
related to finance and banking. In order to properly collect the data and derive insight
from the data, proper data integration is required.
 Real time analytics provides information regarding data in the same time it is
processed. For example when in an ecommerce website a product is out of stock it is
automatically updated in the product list. This requires real time data analytics.
Gap analysis of Collaboration and Teamwork:
1. Explanation of the reason why the theory has been chosen:
According to researchers and industry experts Collaboration and Teamwork is going
to drive the business intelligence and it is hence an important thing to consider. The analysis
of the theory practise gap will provide a valuable insight about the applications and its issues.
Hence this theory has been selected for further analysis to explore the cause of the gap and
how it effects the productivity of the business intelligent system.
2. Analysis of the gap between theory and practice
 According to the theory of collaborative business system there should be perfect
collaboration between the associated analytical tools related to a particular business
intelligent system. It helps the business users to define strategies in collaborative
manner that ensures enhanced productivity (Obeidat et al., 2015). However in practise
the organization often fails to properly execute the collaborative business intelligence
due to lack of proper standard a knowledge gap.
 As the collaboration tolls are difficult to integrate at least what the recent analysis
suggest team work is not effective as well. Hence there is a clear gap between what
the theory suggest and what is actually practised. The reason for this gap has been

5
Gap Between Theory and Practice in Business Intelligence
analysed in details in the following section to identify the root cause (Obeidat et al.,
2015).
3. The root cause of this gap
According to the authors, the root cause behind theory-practise gap is that
organization have very little details about business context that is required by the analytical
data to provide information to the business intelligent system. Along with that organizations
put very little effort on data that ensures strong collaboration (Tarmazdi, 2015). Even
organization finds it difficult to integrate external data, especially data which are not
structured, in a timely and effective way.
As for the team work, the gap exists because of the immense pressure that vendors or
the organization put on the BI team to derive success. The pressure is created on the team to
deliver product in time while meeting all the expectations (Turban, 2014). This is so because
vendors often promise to provide solution to each and every issues that is faced by the
business user and technical team with the tool and the methodology they integrate with their
system. Hence deriving success is an important aspect for any vendor who is providing
solution to business related problems through business intelligence system. Here the
methodology is focused on individual, rather than on team which is the primary requirement
for ensuring an effective team work.
4. The effect of the gap
 Whom or what does it impact?
The gap impacts organization who considers to integrate business intelligent
system to enhance the decision making process through the BI system. If the BI
system is not effective it will affect the decision making process which impacts the
business and customer related decision which means less effective consumer support

6
Gap Between Theory and Practice in Business Intelligence
which means less profit as well (Vogel et al., 2017). So the gap not only impact the
process at organization level, it impacts the customer and the vendors as well who is
responsible to implement the system for the organization.
 Is it a positive or negative impact?
The impact is a negative one as it affects the decision making process which
means less productivity and success in business for the organization or the different
stakeholders such as vendors and customers. Business intelligent system is intended to
have a positive impact on the decision making process with insight about business
process regarding market status, consumer base, product innovation and several other
business related applications. However the theory-practise gap affects this process and
rather have a negative impact on the business process.

7
Gap Between Theory and Practice in Business Intelligence
References:
Jaklič, J., Grublješič, T., & Popovič, A. (2018). The role of compatibility in predicting
business intelligence and analytics use intentions. International Journal of
Information Management, 43, 305-318.
Koch, R. (2015). From business intelligence to predictive analytics. Strategic Finance, 96(7),
56-58.
Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence,
analytics and data science. International Journal of Information Management, 36(5),
700-710.
Obeidat, M., North, M., Richardson, R., Rattanak, V., & North, S. (2015). Business
intelligence technology, applications, and trends. DigitalCommons@ Kennesaw State
University.
Tarmazdi, H., Vivian, R., Szabo, C., Falkner, K., & Falkner, N. (2015, June). Using learning
analytics to visualise computer science teamwork. In Proceedings of the 2015 ACM
Conference on Innovation and Technology in Computer Science Education (pp. 165-
170). ACM.
Turban, E., Sharda, R., Delen, D., & Efraim, T. (2014). Decision support and business
intelligence systems (Vol. 9). Pearson.
Vogel, K. M., Jameson, J. K., Tyler, B. B., Joines, S., Evans, B. M., & Rendon, H. (2017).
The Importance of Organizational Innovation and Adaptation in Building Academic–
Industry–Intelligence Collaboration: Observations from the Laboratory for Analytic
Sciences. The International Journal of Intelligence, Security, and Public
Affairs, 19(3), 171-196.