1. IMT500 Foundations Of Information Management
Answers:
Introduction
Information security is a process of safeguarding organisational data from unauthorised
access. Businesses use several tools and methods to secure their confidential data from
unauthorized attacks. Information data management is a way of managing stakeholders'
data in a congruent manner so that market competitors, hackers and other sources cannot
get into the access of those data. Information security is associated with the prevention of
unauthorised access, disclosure, disruption, inspection, and modification and information
destruction. Data management is performed to protect organisational activities and
confidential data from theft, breaches, data losses and encryption activities. Strong data
security allows businesses to back up their data adequately.
The study is going to analyse the impact of data management and information security in
safeguarding an organisational framework. An example of Walmart will be added in this
regard. The selected company uses big data analysis to increase their sales capacity and
customer loyalty. The section is going to see the implementation of new IS and IDM
strategies to strengthen their business infrastructure. The idea is to diversify the business
activities by involving maximum security and privacy policies.
Theoretical Background
Information security deals with safeguarding organisational data and processes in a
systematic way using relevant tool sets. Several theories can be supported to understand
the use of information management and its necessity. Some of the theoretical headings
under this topic are mentioned below,
Information management: "Information management" deals with the management of
security breaches, disruption, inspection, alteration, and loss of sensitive data. Data
management is used to protect confidential information and functions of the organization
against theft, leaks, and data leakage (Qi, 2020). Businesses can back up their data properly
while maintaining solid data security. This procedure entails gathering, collecting,
organising, protecting, verifying, and processing critical business data. This is a new field
2. that deals with the architecture that is used to gather, administer, retain, preserve, and
deliver data. The guiding principles ensure that the appropriate information reaches the
right people at the right time. All records and information activities for a business are
planned, organised, structured, processed, controlled, and evaluated under this heading. All
of these elements are necessary for corporations and their business types that rely on that
knowledge to operate efficiently.
Information technology: Information technology brings business innovation. Innovative
attributes result in smarter applications, improved data storages, faster processing and
wider data distribution (Chen et al. 2019). Business innovation is required to add unique
features within the process. Innovative attributes make a business efficient and effective in
nature. Information technology helps the organisation to balance the innovative properties
by increasing its value, quality and productivity. This aids in the development and
expansion of the commerce and commercial sectors, resulting in the highest potential
output. With advancements in IT, the time it takes for diverse industries to produce
business is now reduced. It offers security systems, stability, and communication efficiency.
This is important to include within a business to improve business agility, staff
coordination, automation, revenue stream, financial savings, customer experience and much
more.
Information security: "Information security" refers to the process of protecting company
systems from unauthorized access (Yao and Li, 2018). Businesses employ a variety of tools
and approaches to protect their sensitive information from unauthorised access.
Unauthorized access, exposure, interference, surveillance, alteration, and destruction of
information are all examples of information security. This is a collection of procedures for
protecting personal information against unwanted access and alteration while it is being
stored or transmitted from one location to another. It is used to safeguard data against
unauthorised access, exposure, deletion, manipulation, and disturbance. This tool focuses
on maintaining a balance between secrecy, integrity, and accessibility. Information security
is needed to reduce the risk factor of data breaches by cutting off the attacks within the IT
framework. Application of data security controls help to prevent unauthorised access to the
sensitive information (Peeters and Widlak, 2018). Prevention of disrupted services helps in
protecting IT systems and networks from outside exploitation.
Information data management: "Information data management" is a method of managing
stakeholders' data in a consistent manner, preventing market competitors, hackers, and
other outside sources from gaining access to it. Security breach, exposure, disruption,
inspection, alteration, and loss of sensitive data are all examples of "information security".
Data management is done to secure confidential data and organisational activities against
theft, leaks, data leakage, and protection. Businesses can appropriately back up their data
with strong data security. This process involves collection, storing, organisation, protection,
verification and processing of essential business data (Dimitrov, 2019). Data management
helps to make an organisational structure productive and useful. This makes the process
3. easier for the employees to find and understand the data that they require to perform their
job. This allows staff to easily validate results by concluding their business outcomes. Data
management provides the data structure to be easily shared with others involving
confidentiality. This is a way of allowing data to be stored for future reference, which can be
easily retrieved. It has the potential to make the company more cost-effective. This is
because it will assist the company to prevent unneeded redundancy (Vo et al. 2018).
Employees will never undertake the same research, analysis, or task that has been
accomplished by another individual because all data is stored and easily accessible.
Data quality management: This is a way of providing context-specific systems for improving
data fitness, which is used to analyse data by the adoption of adequate decisions. The target
is to create insights into the quality of that data using several technologies on greater and
more complex data sets. This is a business idea principle that calls for a confluence of the
correct people, procedures, and technologies, all with the purpose of increasing the most
important data quality metrics for an organisation (Gomes et al. 2020). "Customer
relationship management" is the most important attribute of any business and data quality
maintenance comes as one of the topmost priorities of this business section.
Data governance: This is a collection of processes, policies and strategies that ensure
efficient utilisation of data by enabling organisations to achieve their goals. This defines
individuals, who can take actions, in what situation or using what methods depending on
what data. Data governance is a way of helping organisation to ensure that the information
is usable, protected and accessible. This plays a major role in regulating compliance that the
institution is compliant with all standards of regulatory requirements. This is a key to
minimising risk and cutting off business costs. This procedure applies to the people,
processes, and information needed to guarantee that data is appropriate for the intended
use.
Data architecture: "Data architecture" is a framework for how business data strategy is
supported by your IT infrastructure (Shamim et al. 2019). The purpose of any "data
architecture" is to explain how data is gathered, transferred, stored, queried, and secured
inside a sustainable framework. Any marketing plan must start with data architecture. This
is a collection of principles made up of precise methods, rules, concepts, and regulations
that govern what kind of content is obtained, where it is gathered, how the data is obtained,
how it is stored, how it is used, and how it is entered into platforms.
Description Of The Case
The company's "Management Information System," which oversees organisational activities
and data confidentiality, is one of its strongest assets (Li et al. 2019). This aids managers in
spotting business flaws and possibilities. This can easily handle information security,
database management, and other applications. The company procures materials directly
from the manufacturers, which helps to reduce business cost. The firm to manage their
4. information uses the EDI model. This model enables managers to download store details
and order details. The IT team and communication system effectively track each sales and
merchandise inventories of the company.
Research Method And Data Collection
Research methods are helpful to identify the research requirements. The goal is to collect
data that can add authentic information regarding the chosen topic. Selection of
methodological tools helps the researchers to include relevant data that can guide readers
having a complete idea of the chosen topic. Detailed methodological discussion has been
added to the below section.
Research Philosophy
The methodological tool can be used to perform a detailed analysis of the data they have
chosen. This part will include a metatheoretical analysis, which is the most fundamental
component of the data collecting. This will be aided by the selection of an appropriate
research philosophy (Žukauskas et al. 2018). The goal is to find objective solutions by
seeking to detect and work around biases in theories and knowledge developed by
theorists. In this case, "post-positivism" will be used to meet the study's goals.
Justification
This research philosophy is implemented to ensure that readers have a thorough
understanding of the research findings. The tool of choice will generate a flexible research
framework to justify each data finding from various sources. The choice will be made after
reviewing the study criteria. This philosophy will aid researchers in establishing that a
researcher's opinions, and even their personal identity, affect what they see and, as a result,
what they discover.
Research Approach
The research strategy refers to the goals that are covered in a study. This tool will assist in
the inclusion of crucial data and a detailed discussion of the issue (Bartelink et al. 2018).
The goal is to compile relevant data based on a fictitious knowledge of the data. Researchers
will be able to create their findings in a methodical manner if they use the right research
approach. This section will use a "deductive" strategy to finish the research.
Justification
This method will aid efficient analysis of data from various sources. This section will
present a thorough data analysis based on field data. Researchers will be able to use this
tool to incorporate a wide range of data into their research. This part may feature an in-
5. depth hypothetical justification of the acquired data sets inside his study, depending on the
study's methodology, which would not have been achievable using an "inductive" approach.
Research Design
The purpose of research design is to embellish collected data so that readers can get a clear
picture of the chosen issue. This methodological tool aids the project in locating the most
appropriate data sources and systematically incorporating them into the area (Sovacool et
al. 2018). Based on data observations, this methodological equipment tackles the indicated
problem by developing the most efficient structure possible. This decision is critical since
no research may have a specific structure unless the design is finalised.
Justification
This tool is used to create a good research framework that includes all of the relevant data.
The research will be aided by "descriptive" design. Following this research design will make
it much easier to get a strong conclusion. This choice was taken in order to offer as much
descriptive analysis as possible. The researchers will focus their efforts on identifying the
situation's flaws in order to determine the industry's exact state at this moment. The
researchers will be guided by the selection to give a comprehensive grasp of the topic.
Data Collection And Data Analysis
The research has followed “qualitative” data analysis to gather data regarding the
importance of data management in the chosen firm. In this regard, the research has picked
some participants from the company to note their opinion in this matter (Lowe et al. 2018).
Two junior managers are picked for the interview. Permission has been taken from the
company before picking participants for this data collection process. Quantitative survey
has not been performed due to the requirement of larger sample size. The researchers have
a limited time to perform the task, which is why they have gone with the interview. Four
open-ended questions will be asked to each of two managers. Their responses will be
analysed and compared to reach a solid conclusion.
Sampling
This research is going to involve four open-ended questions, which makes the sample size
four. Two junior managers are selected for this study, making the research population two.
Each four questions are asked to these individuals to note their opinions regarding the
matter, which has made the research easier to understand and interpret.
Findings
Q1) Do you think having a strong information system is necessary to set up a business?
6. Manager 1
Without a strong information system, no firm can establish a successful business according
to me. This helps us to adopt suitable decisions for the business at an appropriate time. That
is why this is required.
Manager 2
This is one of the most important parts of any business. This helps managers to identify the
business loopholes and opportunities. Information security, database management and
other applications can be easily handled by this.
Q2) Does Walmart come up with an adequate IS tool?
Manager 1
"Management Information System" is one of the biggest strengths of the company, which
controls organisational activities and its data confidentiality.
Manager 2
The firm to control the organisational structure and function uses mIS. This is entirely
efficient to manage daily information within the operational activities of the organisation.
Q3) Does the company come up with proper information security to safeguard business
information.
7. Manager 1
Yes, the firm has proper IS features that are used to store clients' and other stakeholders'
information. The IT team works hard to keep confidentiality of the entire business
framework.
Manager 2
The company has a strong IS framework to control data confidentiality. Managers get
advanced guidance from the team to control the entire business activities.
Q4) Do you believe the firm requires any improvement within the IS framework?
Manager 1
Walmart is one of the biggest names in the retail industry and the staffs receive all kinds of
cooperation while working. The IS and IDM features are working great. According to me, the
firm requires no further improvisations.
Manager 2
A little advancement can be added within these systems. However, the existing system is
working too well for the firm.
Table 1: Analysis of Interview responses
Discussion And Reflection
As per the understanding, both of the managers believe that the company is doing well with
8. their existing framework of information system and information data management. One of
them says that a little advancement may have offered better results. However, he agrees on
the efficiency of the current system. Walmart has a "management information system",
which helps their managers to identify their service loopholes and market opportunities by
providing appropriate data from the regular information system according to the analysis
(Schöpfel et al. 2018).
The research is going to help in understanding the importance of IS, IT and IDM hugely. I
have to know about the MIS framework and its contribution to Walmart. Qualitative data
analysis has helped me to gain a deeper understanding of the topic.
Conclusion
The report has provided details of information data management and information security
taking an example of Walmart. The target of the study is to offer details of these applications
by which the company gets to safeguard their confidential data and essential business
strategies. The selected participants have shared their opinions regarding the matter, which
shows their satisfaction working in the firm. It can be concluded that the company runs a
successful business by efficient utilisation of the MIS and EID model.
References
Bartelink, N.H., Van Assema, P., Jansen, M.W., Savelberg, H.H., Willeboordse, M. and Kremers,
S.P., 2018. The healthy primary School of the Future: a contextual action-oriented research
approach. International journal of environmental research and public health, 15(10),
p.2243.
Chen, J., Lv, Z. and Song, H., 2019. Design of personnel big data management system based
on blockchain. Future Generation Computer Systems, 101, pp.1122-1129.
Dimitrov, D.V., 2019. Blockchain applications for healthcare data management. Healthcare
informatics research, 25(1), pp.51-56.
Gomes, V.C., Queiroz, G.R. and Ferreira, K.R., 2020. An overview of platforms for big earth
observation data management and analysis. Remote Sensing, 12(8), p.1253.
Li, X., Huang, X., Li, C., Yu, R. and Shu, L., 2019. EdgeCare: leveraging edge computing for
collaborative data management in mobile healthcare systems. IEEE Access, 7, pp.22011-
22025.
Lowe, A., Norris, A.C., Farris, A.J. and Babbage, D.R., 2018. Quantifying thematic saturation in
qualitative data analysis. Field Methods, 30(3), pp.191-207.
9. Peeters, R. and Widlak, A., 2018. The digital cage: Administrative exclusion through
information architecture–The case of the Dutch civil registry's master data management
system. Government Information Quarterly, 35(2), pp.175-183.
Qi, C.C., 2020. Big data management in the mining industry. International Journal of
Minerals, Metallurgy and Materials, 27(2), pp.131-139.
Schöpfel, J., Ferrant, C., André, F. and Fabre, R., 2018. Research data management in the
French national research center (CNRS). Data technologies and applications.
Shamim, S., Zeng, J., Shariq, S.M. and Khan, Z., 2019. Role of big data management in
enhancing big data decision-making capability and quality among Chinese firms: A dynamic
capabilities view. Information & Management, 56(6), p.103135.
Sovacool, B.K., Axsen, J. and Sorrell, S., 2018. Promoting novelty, rigor, and style in energy
social science: towards codes of practice for appropriate methods and research design.
Energy Research & Social Science, 45, pp.12-42.
Vo, H.T., Kundu, A. and Mohania, M.K., 2018, March. Research Directions in Blockchain Data
Management and Analytics. In EDBT (pp. 445-448).
Yao, X. and Li, G., 2018. Big spatial vector data management: a review. Big Earth Data, 2(1),
pp.108-129.
Žukauskas, P., Vveinhardt, J. and Andriukaitien?, R., 2018. Philosophy and paradigm of
scientific research. Management Culture and Corporate Social Responsibility, 121.
