Organizational Data Management Problem: Research and Evaluation

This report addresses the challenges of organizational data management, emphasizing its critical role in business intelligence and decision-making. It identifies data management problems, such as issues with data consistency and the impact on data warehousing. The report examines the importance of effective data management for minimizing errors, improving efficiency, and enhancing data quality. It evaluates the impact of these problems on business intelligence practices, including the use of data mining and real-time data warehousing. The study further explores the reasons behind these problems, such as the lack of uniqueness in reference tables and the lack of version management. Finally, the report evaluates several articles related to the subject and concludes with the importance of investing in effective business intelligence systems to share information across departments and gain competitive advantages in the market, highlighting tools such as Sisense, Looker, and Tableau.

Running head: ORGANIZATIONAL DATA MANAGEMENT PROBLEM
Evaluate the Research and its Impact on Databases and Business Intelligence Practice/
Organizational Data Management Problem
Name of the Student
Name of the University
Author note:

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Table of Contents
Introduction..........................................................................................................................2
Identification of the organizational data management problem..........................................2
The impact of the problem...................................................................................................4
The reason for exist the problem.........................................................................................6
Evaluation of the articles.....................................................................................................6
Conclusion...........................................................................................................................7
Reference.............................................................................................................................8

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Introduction
In any organization, data is considered as the major foundations of information,
knowledge as well as ultimate wisdom for making correct decisions and actions. Data
management is the function of planning, controlling and delivering data effectively in the
enterprise. Effective data management can be helpful to minimize errors, improve efficiency,
protection from data related issues and risks and enhance the quality of data. In the present study,
the organization data management has been discussed along with the impact of the problem. In
addition, the reason for existing the issue and evaluation of the articles are discussed in the study.
Identification of the organizational data management problem
Bell, Bryman, and Harley (2018) stated that it is important to deliver customer value as
well as creating competitive benefits required by an organization in order to acquire information
external to the enterprise. The sales of the organization interact directly with external
environment customers and competitors along with another market. On the other hand, social
business intelligence has emerged as one of the major components of a business organization.
The innovation of IT has been forced taking responsibility for cloud data management as well as
cut costs of business. There are 69% of organizations believed that data protection; privacy as
well as compliance is the responsibility of cloud service provider (Wamba et al., 2017). It has a
significant effect on data breach as well as regulatory compliance.

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Figure 1: Data management cycle
(Source: Wamba et al., 2017, p.564)
On the contrary, electronic ticket provider services are increasing fast that makes
competition between the organizations (Wamba et al., 2017). In addition, most of the
organizations include the same type of services to provide service to the customers. The growth
of present technology allows the organization taking data from social media. Hence, the
organizations take social media data to make an analysis. Apart from these, the data warehouse
developed for travel organizations provides the comparison of performance based on social
media data (Sallam et al., 2014). In order to explore present information as well as react faster to
the changing business conditions, enterprises consider real-time data warehousing technique for
achieving operational business intelligence.

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The impact of the problem
The organizations are realizing potential value in sharing intelligence through a common
form of gaining intelligence. However, the most general form of gaining intelligence for buying
data from a third party and not sharing intelligence with the competitors along with third parties.
The private organizations will be helpful to mark documents, reports as well as analysis, which
are sold to others for buying data from a third party. In market intelligence, it is the type of data
helps the organizations gathering data (Abbasi, Sarker & Chiang, 2016). From the perspective of
intelligence, studies have a intelligence as a service is considered as a more interesting domain
for exploring compared to data as a service. It is one of the web-based services whether it is
important to bring web-based service.
Business information, as well as business analysis in the business processes, are
considered as the key components that lead to the process of decision-making and actions. It
leads to enhance business performance. Business intelligence applications can allow users using
more applications and reliable information as well as knowledge. In addition, business
intelligence helps to take a timely decision (Soto-Acosta et al., 2016). Dynamic decisions are
taken rapidly. The findings gained by the enterprise are the organization that will process the
ability reacting constantly according to the movements.

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Figure 2: Data management through data warehousing
(Source: Soto-Acosta et al., 2015, p.465)
Mitri and Palocsay (2015) stated that processing data commented from Facebook and
Twitter, social media is achieved through the processing of converting words. As data warehouse
is integrated and subject-oriented, non-volatile database as well as time-variant. It can provide
support to the process of decision-making (Sallam et al., 2014). It is explained as the database,
which can store present as well as historical data of the possible interest to the managers of the
organization. The data from internal sources are generally combined with the data from external
sources along with recognized into a central database. It is designed for reporting of management
and analysis. Data mining is utilized in order to perform data analysis for discovering the
unknown data characteristics, dependencies, and relationships (Soto-Acosta et al., 2015). The
tools of data mining can initiate analysis of creating knowledge. The organizations require

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managing data assets carefully in order to ensure that the process is evaluated as well as utilized
by employees and managers across the levels of the organization.
The reason for exist the problem
Use of market intelligence, it is required to develop an economic model in order to
capture the specific pattern of producing as well as sharing market intelligence throughout the
social network of the organization. On the other hand, business intelligence becomes inseparable
from information technology systems and big data, There are several suppliers like to see actual
intelligence as they are afraid of making own analysis (Shollo & Galliers, 2016). Through,
analyzing the data from the articles it can be stated that lack of uniqueness of the reference table
in distributed on various servers that cause loss of information existing in the identification
documents of the same source with several points. In addition, lacks of management of the
versions, as well as revisions that are specified, are the collaborators that are accessed for various
information of the same source.
Evaluation of the articles
In present years, the amount of information has been increasing within the organizations.
Hence, several organizations have deployed analytics as well as business intelligence for the
solutions (Fraj, Matute & Melero, 2015). The emergence of business intelligence and tools can
improve business decision-making process through providing ability to compare actual as well as
planned performance (Trumpy et al., 2015). However, business intelligence and performance
management of the business can processes data in the data warehouse, which is considered as the
issues outlined I the direct access to the business transaction data. On the other hand, the
summarized data can be managed in an organization of data warehouse. The performance issues

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of data caused through centralization of data can solve the performance issues through spreading
business intelligence processing in the multiple stores.
There are several articles written regarding the issues of developing independent data marts
directly from the operational data. The CDR data is considered as a different situation. CDR
information is utilized for identifying fraud and quicker analysis (Sallam et al., 2014). The
instance of the type of processing is considered as trading operations. Business applications can
analyze web. The applications of capturing data and tracking the applications to analyze the
process are important in the organizations. Hence, it is required to analyze the issues properly
that and take appropriate actions so that data management problems can be solved. Tools of
business intelligence can be helpful to analyze the issues and solve the issues.
Conclusion
The issues involved with data marts is developed directly from databases of the business.
In addition, it is quicker for the organization rather than data warehouses. Several types of data
are disconnected with the data warehouse along with the data marts leading to face issues in data
consistency. Investing in effective business intelligence system is significant for an enterprise as
it helps to improve efficiency of the organization. The business intelligence can be helpful to
share information across multiple department of the organization. Hence, use of business
intelligence tools like sisense, looker and tableau are helpful to bring competitive benefits in the
market.

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Reference
Abbasi, A., Sarker, S., & Chiang, R. H. (2016). Big data research in information systems:
Toward an inclusive research agenda. Journal of the Association for Information
Systems, 17(2).
Bell, E., Bryman, A., & Harley, B. (2018). Business research methods. Oxford university press.
Chae, B. K. (2015). Insights from hashtag# supplychain and Twitter Analytics: Considering
Twitter and Twitter data for supply chain practice and research. International Journal of
Production Economics, 165, 247-259.
Chen, D. Q., Preston, D. S., & Swink, M. (2015). How the use of big data analytics affects value
creation in supply chain management. Journal of Management Information
Systems, 32(4), 4-39.
Shollo, A., & Galliers, R. D. (2016). Towards an understanding of the role of business
intelligence systems in organizational knowing. Information Systems Journal, 26(4), 339-
367.
Fraj, E., Matute, J., & Melero, I. (2015). Environmental strategies and organizational
competitiveness in the hotel industry: The role of learning and innovation as determinants
of environmental success. Tourism Management, 46, 30-42.
Mitri, M., & Palocsay, S. (2015). Toward a model undergraduate curriculum for the emerging
business intelligence and analytics discipline. Communications of the Association for
Information Systems, 37(1), 31.

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Sallam, R. L., Tapadinhas, J., Parenteau, J., Yuen, D., & Hostmann, B. (2014). Magic quadrant
for business intelligence and analytics platforms. Gartner RAS core research notes.
Gartner, Stamford, CT.
Soto-Acosta, P., Popa, S., & Palacios-Marqués, D. (2016). E-business, organizational innovation
and firm performance in manufacturing SMEs: an empirical study in
Spain. Technological and Economic Development of Economy, 22(6), 885-904.
Trumpy, E., Bertani, R., Manzella, A., & Sander, M. (2015). The web-oriented framework of the
world geothermal production database: a business intelligence platform for wide data
distribution and analysis. Renewable Energy, 74, 379-389.
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big
data analytics and firm performance: Effects of dynamic capabilities. Journal of Business
Research, 70, 356-365.
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