IT Infrastructure Management: Electronic Records, BI, Cloud Computing, and More

This article discusses various aspects of IT infrastructure management, including electronic records management, business intelligence and analytics, data and text mining, cloud computing, and more. It covers the benefits and challenges of these technologies and provides insights into how they can be used to create business value. The article also discusses issues related to executive information systems, processing POS data, and creating favorable customer experiences.

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

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Table of Contents
Question 1..................................................................................................................................2
Question 2..................................................................................................................................4
Question 3..................................................................................................................................5
Question 4..................................................................................................................................7
Question 5..................................................................................................................................8
References..................................................................................................................................9

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Question 1
i) Electronic Records Management: The set of actions that is required to
systematically control the distribution, usage, maintenance, disposition and creation of all
types of records that include the various procedures to capture and maintain evidence is
known as ERM (Nguyen, Newby & Macaulay, 2015).
ii) Business Intelligence (BI) and Analytics: BI is the technology driven procedure to
analyze data or information and presenting the actionable data or information for helping the
managers, executive as well as corporate end users to take business decisions.
The practice of methodological and iterative exploration of the data of the company
with providing an emphasis on the statistical analysis is termed as business analytics.
iii) Data and Text Mining: The procedure to discover the patterns for larger data sets
for the intersection of database systems, statistics and machine learning is known as data
mining (Tafti, Mithas & Krishnan, 2013).
The procedure to derive the high-quality data from texts by devising the high quality
data from the texts is known as text mining. Statistical pattern learning is one of the best
means to devise these patterns.
iv) Big Data Analytics and Data Recovery: The large amount of data is easily
harnessed and then utilized for identifying the new opportunities with the help of big data
analytics (Ullah & Lai, 2013).
The method to retrieve corrupted, damaged, lost or the inaccessible information from
any kind of removable medium or file is termed as data recovery.

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v) Enterprise Architecture: The enterprise architecture is a conceptual blueprint,
which could eventually define the structure as well as operation of the company (Tiwana,
Konsynski & Venkatraman, 2013). The current and the future objectives are achieved
effectively with the enterprise architecture.
vi) Management Information System: The kind of information system, which is
utilized for taking decisions and executes information operations in any company, is termed
as management information system.
vii) Data Life Cycle and Data Principles: The significant sequence of the steps,
which any specific data unit goes from the initial stage or capturing the events, is known as
data life cycle (Hills, 2018).
The eight principles that are used for governing or analyze the data or strategies are
together termed as data principles.
viii) Cloud Computing: The significant technology that helps in delivering the
various hosted services from one location to the other via Internet is termed as cloud
computing (Carlin & Curran, 2013).

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Question 2
Data and text mining helps to create significant business value for all organizations
(Nguyen, Newby & Macaulay, 2015). This method uses the most noteworthy processes for
this purpose and all these processes are provided below:
i) Information Extraction: The procedure to extract meaningful information from the
huge chunks of data after focusing on the identification of attribute and entity extraction is
known as information extraction.
ii) Information Retrieval: The second process for extracting associated or relevant
patterns on the basis of typical phrases or sets (Tafti, Mithas & Krishnan, 2013). Various
algorithms are used in this process for tracking or monitoring the data.
These two processes are extremely important for the data and text mining to create the
respective business values.

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Question 3
Cloud computing is the most popular technology for transferring sensitive data via
Internet (Pearson, 2013). The few vital and noteworthy problems with the cloud computing
technology are as follows:
i) Difficulty in migrating data or any other service.
ii) Extremely Costly.
iii) There is no security for data.
iv) Breaching of data is common.
v) Enables Insider Threats (Hwang, Dongarra & Fox, 2013).
These five cloud problems could be extremely vulnerable for the users. However,
amongst these problems, two examples are insider threats and data breaching.
i) Enabling Insider Threats: The insider threats are the most dangerous problems for
any cloud user. It occurs when the employees of the company are exploiting or destroying the
information either accidentally or deliberately.
The only way to solve this specific cloud computing issue is by providing training to
the employees and increasing the security measures so that the employees does not get any
chance to exploit the data.
ii) Data Breaching: The second cloud problem example is data breaching (Carlin &
Curran, 2013). The data breaching makes it difficult for the intended users to eventually
maintain the integrity or confidentiality of data. Furthermore, data recovery is also difficult in
such cases.

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Data breaching within the technology of cloud computing could be stopped by the
physical space security and by deploying antivirus and firewalls.

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Question 4
i) Reason to Design and Implement EIS: The executive information systems were
designed and also implemented for providing two types of data to the senior management.
Furthermore, the respective KPIs were recognized in the procedure.
ii) EIS Issues: The major issues with the executive information system were to be
solved under any circumstance. The first EIS issue was the unavailability of the half data
through this information system. Moreover, since the time frames were different; hence sales
revenue calculation was difficult.
iii) Causes for EIS Issues: The major cause for the EIS failure in this organization
was that the IT architecture was infeasible as per design and thus only the financial reports
were noted. The user interfaces were much complex in this information system and hence the
executives could not review KPIs.
iv) CIO Improved EIS: The chief information officer in this company has completed
the work with other staffs to design or deploy the newer EIS. The various policies as well as
procedures of the governance of data were substantially deployed for standardization of data
formats.
v) Advantages of the new IT Architecture: This total consumption of time could be
easily eliminated with this new architecture and thus adhoc analysis was also not required any
more.
vi) Advantages of the Data Governance: The data governance helps in easy data
management for validation of data accuracy according to requirements and standards.

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Question 5
i) Importance of Processing POS Data: This Coca-Cola Company should develop
real time POS data for supporting their supply chain forecasting, planning or replenishment
procedure.
ii) Creating Favourable Customer Experiences: This could be done by
implementation of few strategies like creation of customer’s experience visions, utilizing
quality framework, knowing about the target customers and much more.
iii) Significance of Trusted Data View: The data becomes cost effective and
manageable and this is the trusted data view in Coca-Cola.
iv) Black Book Model: The complexities of orange juice decision model are reduced
with black book model for quantifying the relationship between variables.
v) Strategic Benefits of Black Book Model: More than six-hundred flavours’ data are
combined together after involving weather change, rate of sweetness, cost pressure, customer
preferences, crop yields, orange making and preferences of regional customers.

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References
Carlin, S., & Curran, K. (2013). Cloud computing security. In Pervasive and Ubiquitous
Technology Innovations for Ambient Intelligence Environments (pp. 12-17). IGI
Global.
Hills, J. (2018). Information technology and industrial policy. Routledge.
Hwang, K., Dongarra, J., & Fox, G. C. (2013). Distributed and cloud computing: from
parallel processing to the internet of things. Morgan Kaufmann.
Nguyen, T. H., Newby, M., & Macaulay, M. J. (2015). Information technology adoption in
small business: Confirmation of a proposed framework. Journal of Small Business
Management, 53(1), 207-227.
Pearson, S. (2013). Privacy, security and trust in cloud computing. In Privacy and Security
for Cloud Computing (pp. 3-42). Springer, London.
Tafti, A., Mithas, S., & Krishnan, M. S. (2013). The effect of information technology–
enabled flexibility on formation and market value of alliances. Management
Science, 59(1), 207-225.
Tiwana, A., Konsynski, B., & Venkatraman, N. (2013). Special issue: Information
technology and organizational governance: The IT governance cube. Journal of
Management Information Systems, 30(3), 7-12.
Ullah, A., & Lai, R. (2013). A systematic review of business and information technology
alignment. ACM Transactions on Management Information Systems (TMIS), 4(1), 4.