IT Infrastructure Management PG

This assignment provides detailed answers to various questions related to IT infrastructure management, including electronic record management, data mining and text mining, cloud computing, executive information systems, and more. The answers cover topics such as the importance of data governance, the benefits of using EIS, and the need for proper data security in cloud computing.

Running head: IT INFRASTRUCTURE MANAGEMENT PG
IT Infrastructure Management PG
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1IT INFRASTRUCTURE MANAGEMENT PG
Table of Contents
Answer 1..............................................................................................................................2
Answer 2..............................................................................................................................3
Answer 3..............................................................................................................................4
Answer 4..............................................................................................................................4
Answer 5..............................................................................................................................5
References............................................................................................................................7

2IT INFRASTRUCTURE MANAGEMENT PG
Answer 1
1. Electronic record management is a process of maintaining records in an electronic
platform be it cloud or by making use of different digital devices. Electronic record
management has certain advantages over traditional record management as it eliminates
the problems of data inconsistency and data duplication. Furthermore, it becomes easier
to sort and search for a data from an electronic record management system.
2. Business Intelligence is a broad concept and refers to different technologies, application
and practices for analyzing a group of data, which in turn helps the executives and the
managers in taking proper business decisions. Business Analytics on the other hand is an
iterative approach of exploration of the organization’s data in form of statistical analysis
of the collected data. It helps an organization in undertaking a data driven decision-
making approach.
3. Analyzing a large volume of data in order to obtain certain crucial information that might
helps an organization in improving their decision-making process is known as data
mining (Witten et al., 2016). Text mining is equivalent to data mining as well. However,
it deals with the analysis of large number of unstructured data. Quality information can
be derived from data mining and text mining that helps in devising better business plans.
4. The process of examining a large and varied data set is termed as business analytics. It
helps in uncovering the current business trends and market preferences, which in turn
helps in designing a better business plans (Kambatla et al., 2014). Therefore, business
analytics is a process that helps an organization in undertaking a more informed business
decisions. Data discovery on the other hand refers to the process of deriving and

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collecting data from various different databases and ultimately combining the collected
data into a single source. This helps in instant evaluation of the collected data.
5. Enterprise architecture is a process of creation of a unified IT environment in a business
organization. It helps in mapping the IT assets present in an organization to plan its
strategic use within the organization. It links several business units with the set
organizational strategy in order to facilitate the different business processes running
within the organization.
6. Management information system refers to the processing of the information with the help
of different digital devices. Transaction processing system and decision support system
are two examples of management information system (Laudon & Laudon, 2016). It
provides a computerized database of financial information and generation of regular
reports, which helps in better management of an organization.
7. The overview of the stages starting from data creation to the deletion of data is known as
data life cycle. It refers to the sequence of stages a data goes through after its initial
generation to its deletion. Data principle refers to the fair and responsible use of data.
There are eight principles of data discovery that defines the fair and responsible use of
personal data or information
8. The concept of storing data and information in a network of servers that is hosted over
internet is known as cloud computing (Dinh et al., 2013). It is an on demand delivery of
the computing services including the servers, storage and databases. It is an information
technology paradigm for enabling ubiquitous access to the pool of configurable
resources.
Answer 2

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Data mining and text mining provides certain business values to an organization. Data
mining is a process of unveiling the hidden patterns in the business including customer
preferences and current market trends. Understanding the customer preferences helps in refining
the business processes of the organization (Wu et al., 2014). Furthermore, analyzing through a
large number of structured and unstructured data helps in understanding the different business
trends and risks associated with a business. Therefore, it can be said that the process of data
mining and text mining brings good values to an organization.
Answer 3
The main problems associated with cloud computing is data security issues and issues
with the use and access of data through cloud. Example of data security issues includes data
breach and unauthorized access of data (Chen & Zhao, 2012). Example of problem in data access
includes denial of service attack.
These two problems can be mitigated by employing proper security features into the
cloud computing system. The data stored into the system should be encrypted and protected by
authorization control (Arora, Parashar & Transforming, 2013). The ease of data access can be
enhanced by installing regular security updates into the system.
Answer 4
1. The Executive Information System was implemented to provide the senior managers with
the relevant data for accessing the Key performance Indicators or KPIs.
2. The executives fund out that the data was not available in time of need and it is one of the
major problems faced in EIS by the executives.

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3. The IT architecture was not designed for customized reporting and was based on
financial accounting rules. This was a major problem associated with the EIS. Secondly
the user interface was quite complicated that added up to the problems associated with
EIS.
4. CIO improved the EIS by developing a new enterprise IT architecture with standard data
formats.
5. The business driven new architecture was easy to use and the data produced by the
system was quite reliable. This increased the use of EIS by the executives adding to the
major benefits of the new IT architecture.
6. Proper data governance helps in elimination of data inconsistency, which in turn helps in
providing a reliable KPI report on the different business process of the organization.
Answer 5
1. It is important for Coca Cola to be able to process the POS data in real time as it
will help the company in understanding the customer preferences in a better way,
which would have been not possible by manually searching through the large
amount of data.
2. In order to create a favorable customer experience, Coca Cola switched to a
centralized approach to a decentralized approach in order to address the
customers’ queries in a better way.
3. The trusted data helps in developing accurate results. This in turn helps in
development of accurate business processes and responding to the changes more
accurately.

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4. Black Book model is a decision-making model that stores the details of 600+
different flavors that is required to produce orange juice.
5. The Black Book model helps the company in producing orange juice of consistent
flavor 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.