IT Infrastructure Management PG Assignment

This assignment is focused on various topics related to IT infrastructure management, including electronic record management, business intelligence, data mining, text mining, big data analytics, data discovery, enterprise architecture, management information systems, data life cycle, data principles, cloud computing, EIS (Executive Information System), and more. The assignment questions and answers cover key concepts, challenges, and solutions in these areas, providing valuable insights for students pursuing PG studies in IT infrastructure management.

Running head: IT INFRASTRUCTURE MANAGEMENT PG
IT Infrastructure Management PG
Name of the Student
Name of the University
Author Note

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Table of Contents
Answer 1..............................................................................................................................2
Answer 2..............................................................................................................................4
Answer 3..............................................................................................................................4
Answer 4..............................................................................................................................4
Question 5............................................................................................................................5
References............................................................................................................................7

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Answer 1
1. Electronic record management is a process of management of the different records using
software. It is a process of efficient and systemic process of creation, use, maintenance
and deletion of different records stored within an electronic record management. An
electronic record management system ensures that the records of an organization are
readily available in times of need and is required for systematic control, creation and
maintenance of a system.
2. Business intelligence refers to the use of different strategies and technologies of
providing historical and predictive views of the different business operation. Business
intelligence is a process of accessing and exploring the important data of an organization
in order to support better business decision making. Business analytics on the other hand
is an iterative and methodical exploration of the data of an organization with the help of
statistical data analysis.
3. Data mining is a process of searching through a large database with an aim of discovering
the different patterns and data trends that generally go beyond the simple analysis of the
data. The process of data mining mainly makes use of the sophisticated mathematical
algorithms for proper evaluation of the probability of occurrence of certain future events
in the organization (Witten et al. 2016). Text mining is a process of analysing a data that
is contained in the natural language text. Text mining helps in solving the different
business problems through the process of text analytics.
4. Big data analytics refers to the process of examining a large amount of data for
uncovering the hidden patterns, which in turn helps in analysing the market trends,
customer preferences along with other vital information that helps an organization in

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proper decision making (Kambatla et al., 2014). Data discovery on the other hand
generally refers to a business oriented process of collecting data from different databases.
The process of data discovery is business oriented and is guided by advanced analytics.
5. Enterprise architecture is a well defined practice of conducting the enterprise analysis,
design and implementation of a unified IT environment across the organization. It is a
conceptual blueprint that defines the different structure and operations of an organization.
6. Management information systems can be defined as a computer based system that
provides the tools for the managers in organizing, evaluation and efficient management
of the different departments within an organization (Laudon & Laudon, 2016). The
system is consisted of different hardware and software that serves as the backbone of a
particular organization.
7. Data life cycle is a sequence of stages that gives an overview of the life of a particular
data from its initiation to closure. It is a process of recording, managing and deletion of a
particular data; the entire sequence is termed as data life cycle. Data principles defines
the ethical use of data within an organization
8. Cloud computing is a process of storing data over internet with the help of the remote
servers that are hosted over internet (Dinh et al., 2013). This technology is increasingly
adopted by different business organization as it enhances the data accessibility and saves
a considerable amount of physical storage, as the cloud services are levered by third party
vendors.

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Answer 2
The process of data mining and text mining refers to the analysis of the large amount of
structured and unstructured data in order to gain information about the customers’ preferences,
market trends and other valuable information that can help in improving the business processes
of an organization (Wu et al., 2014). It furthermore helps in creating business values by
identifying the different risks associated with an organization.
Answer 3
Cloud computing is a widely adopted technology of recent times as provides an adequate
solution of storing a large amount of data over cloud. This not only saves a huge amount of
storage space but also helps in making the process of data access easier. However there are
certain problems faced with the use of cloud computing, the major ones being the risk of security
attacks and data loss from an insider or outsider (Chen & Zhao,2012). Since the data is stored
over internet, these problems are majorly faced in cloud computing.
The problems can be mitigated by ensuring proper data protection in terms of encryption
and authorization and authentication. Data protection by encryption ensures only the authorized
members are able to access the confidential information stored over cloud (Arora, Parashar &
Transforming, 2013). Furthermore, limiting the number of persons who can access the system
through authorization will help in preventing any unauthorized data access.
Answer 4

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1. The EIS or executive information system was implemented in the organization to provide
the senior management with the internal and external data along with the associated KPIs
or key performance indicators.
2. The EIS system that was implemented failed to deliver the required data at the times of
need. This hampered the process of effective decision making within the organization.
This is the major problem that the executives had with the EIS.
3. The IT architecture was not designed for customized reporting and the user interface of
the system was quite complicated. These are the two major reasons of those EIS
problems.
4. CIO improved the EIS by developing a new enterprise IT architecture with a standard
data format.
5. The major benefit of the new architecture was that, it followed a business driven
approach instead of the financial reporting driven approach. Furthermore, in the new
system, it was easy to modify the reports.
6. The main benefit of data governance is that it helps in reduction or elimination of data
inconsistency.
Question 5
1. Processing of the POS data in near real time will make the process of data search easier,
which in turn increases the efficiency of the decision making process.
2. In order to create a favourable customer experience, Coca Cola changed its centralized
database system to centralized data system for better data management, which in turn
increases customers’ satisfaction.

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3. Analysis of the trusted data will help in designing proper business strategies within the
organization Coca Cola and therefore, it is essential to have a trusted view of the data.
4. Black Book model of Coca Cola is a software application that stores the details of the
600+ flavours that makes up an orange juice.
5. With the stored details of the flavours, the black book model enables the organization in
developing orange juice of consistent flavour throughout the year.

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References
Arora, R., Parashar, A., & Transforming, C. C. I. (2013). Secure user data in cloud computing
using encryption algorithms. International journal of engineering research and
applications, 3(4), 1922-1926
Chen, D., & Zhao, H. (2012, March). Data security and privacy protection issues in cloud
computing. In Computer Science and Electronics Engineering (ICCSEE), 2012
International Conference on (Vol. 1, pp. 647-651). IEEE.
Dinh, H. T., Lee, C., Niyato, D., & Wang, P. (2013). A survey of mobile cloud computing:
architecture, applications, and approaches. Wireless communications and mobile
computing, 13(18), 1587-1611.
Kambatla, K., Kollias, G., Kumar, V., & Grama, A. (2014). Trends in big data analytics. Journal
of Parallel and Distributed Computing, 74(7), 2561-2573.
Lapalme, J. (2012). Three schools of thought on enterprise architecture. IT professional, 14(6),
37-43.
Laudon, K. C., & Laudon, J. P. (2016). Management information system. Pearson Education
India.
Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine
learning tools and techniques. Morgan Kaufmann.
Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE transactions
on knowledge and data engineering, 26(1), 97-107.