Importance of Big Data Analytics in Business: A Feasibility Analysis

This report presents a feasibility analysis focusing on the importance of Big Data Analytics in business. It explores the role of consultants, summarizing questions posed to an industry representative and their feedback. The analysis delves into the research's significance, justification, proposed methodology, and potential industry applications. The consultant's feedback emphasizes the need for a detailed timeline and project charter to manage risks and ensure efficient task assignments. The report reflects on the consultant's recommendations, highlighting the importance of a structured schedule to streamline the research process and manage stakeholders effectively. The findings underscore the value of Big Data Analytics in enhancing business operations and decision-making, supported by a comprehensive methodology involving interviews and surveys with Australian companies. This research aims to provide a clear understanding of how Big Data Analytics can be effectively implemented to increase the value of an organization.

Running head: FEASIBILITY ANALYSIS
Assignment 2: Feasibility Analysis
Topic: Importance of Big Data Analytics in Business
Name of the Student
Name of the University
Author Note

1FEASIBILITY ANALYSIS
Table of Contents
Role of the Industry Representative or Consultant and their years working in the industry.....2
Summary of the Questions presented to the Industry Representative or Consultant.................2
Summary of Feedback/Recommendation from the Industry Representative or Consultant......4
Reflection on the Feedback/Recommendation...........................................................................4
References..................................................................................................................................6

2FEASIBILITY ANALYSIS
Role of the Consultant and their years working in the industry
The purpose and role of consultant for any research works as an advisory body during
the conduction of the research or even before. The research has to be presented to the
advisory body or the consultant before they are being conducted so that they can look
throughout the entire research plan and proposed plan of collecting metre to study the reports
and identify any issue that might arise as a potential risk (Sahir and Brutus 2018). They
advise the researcher with accurate problem-solving methods, improve the growth regarding
the research, create value and also increase profitability and efficiency through the research.
The consultants during a research conduction analysis and interpret the data that has been
brought about during the research for further data mining. This provides them with probable
identification of relevant information affecting the operations conducted during the research
procedure.
For this research as well, of more than 5 years working in the industry the consultant
is liable to provide the skills and knowledge areas to the research that is being conducted
about the importance of Big Data Analytics in business. The findings of the research mostly
revolve around the probability of getting skilled analysts to the business world for the best
possible and effective Big Data Analytics performed within an industry or an organisation
(Nissen 2019). This is why the consultant will go about questioning each and every
conducted methods and theories taken for the research to find the feasibility of every action
including the importance of the research, the justification to conduct the research, the
proposed methodology and the findings of the study to identify the proper industry
applications.

3FEASIBILITY ANALYSIS
Summary of the Questions presented to the Consultant
Importance of the Research Topic for the industry: The research topic is one of
the very important subjects that organisations are implementing because of the technological
advancements that have involved the digital data collection, management and storage
advance of the most important Assets of the industry (Plotnikova, Dumas and Milani 2019).
This is why it is not just important that people within the organisation are using data for
storage, management and sharing but also, they are effective data analysts that are
appropriately analysing the collected data utilising the big data analysis methods. Change
data is accepted as an asset, business organisations have faced several problems and issues in
handling and analysing the correct information because of problems in finding skill data
analyst. This is why the research topic is not just a recent technological advancement but also
a problem that should be solved for providing benefits to the industry.
How convincing has been the justification of the research: The nationality of the
conduction of the research is given by the ability of tackling the huge income of data and also
employ Big Data Analytics who understand the importance of data within an organisation
and how it can either increase the value of an organisation by reducing the cost, reading faster
decision making system, better and new service and product implementation in the
organisation (Choi, Chan & Yue 2016). It also would justify the analysis of how the opposite
can reduce the value of an organisation and affect its reputation creating customer
dissatisfaction.
Feasibility of the proposed methodology: The methodology that is being used for
this particular purpose is to rely on the gathering of primary data from different sources of
conducting interviews and surveys. The people who be taken as a sampling size would
include the managers of three different Australian companies (Nissen and Seifert 2018). The
techniques that would be applied for this research should be non-probabilistic sampling

4FEASIBILITY ANALYSIS
techniques and simple random sampling method. Analysis of the data would be utilised by
thematic approach for the qualitative data taken from the interview (Deelmann and Nissen
2019). The proposed methodology is feasible since it utilizes open-ended interview questions
so that the managers would be e free of providing their opinion without having a pre-assumed
outcome of the research topic. This is why the proposed methodology would not what have
an assumed conclusion at the end of the research. The thematic approach would help to
analyse the data and information both included in the primary qualitative data collection.
Industry applications of the findings of the study: The applications of the findings
of this research in the industry would provide positive benefits as this would have the
organisation get a clear idea about the concepts of big data and how Big Data Analytics
would add value to the organisation (Seifert and Nissen 2018). Understanding the concept in
details would help them employ the best possible Big Data Analytics in the business.
Summary of Feedback from the Consultant
The feedback on the recommendation that the consultant has presented to this
research is to have a timeline prepared to represent all the activities and their starting and end
point in the research. This would ensure that the entire research is being conducted operation
for changes applied to the research approach when a risk arises (Nissen, Nissen and Rauscher
2019). It demonstrates that the revising of the scope of the topic would not be necessary but a
project charter would have the research understand the key stakeholders associated with the
research. Having a schedule and charter ready during the research would help in proper
assignment of task according to the time frame and also minimises at the same time.
Reflection on the Feedback
I believe that the recommendation that the consultant has provided over the research
is extremely necessary since there might not be much changes that need to be applied to the

5FEASIBILITY ANALYSIS
objectives of the research methods but there are no schedule recorded for all the activities that
needs to be performed one after another. Having a schedule would provide a detailed idea of
which task is to be performed after another and which stakeholder is associated with each of
these subtasks. The starting and ending point is necessary to find out in this research so that
the flow of research procedure is following a specific time frame within the budget reducing
all the associated risk that might occur.

6FEASIBILITY ANALYSIS
References
Choi, T.M., Chan, H.K. and Yue, X., 2016. Recent development in big data analytics for
business operations and risk management. IEEE transactions on cybernetics, 47(1), pp.81-92.
Deelmann, T. and Nissen, V., 2019. Institutionalization of Consulting Research: Review and
Comparison of Two Approaches in Germany Over the Period 2007–2017. In Advances in
Consulting Research (pp. 53-75). Springer, Cham.
Nissen, V. and Seifert, H., 2018. Evaluating the virtualization potential of consulting
services. In Digital Transformation of the Consulting Industry (pp. 191-205). Springer,
Cham.
Nissen, V., 2019. Consulting Research: A Scientific Perspective on Consulting. In Advances
in Consulting Research (pp. 1-27). Springer, Cham.
Nissen, V., Nissen, V. and Rauscher, 2019. Advances in consulting research. Springer
International Publishing.
Plotnikova, V., Dumas, M. and Milani, F.P., 2019, September. Data Mining Methodologies
in the Banking Domain: A Systematic Literature Review. In International Conference on
Business Informatics Research (pp. 104-118). Springer, Cham.
Sahir, R. and Brutus, S., 2018. A view of the role of expert in corporate
consulting. Consulting Psychology Journal: Practice and Research, 70(2), p.95.
Seifert, H. and Nissen, V., 2018. Virtualization of consulting services: state of research on
digital transformation in consulting and future research demand. In Digital Transformation of
the Consulting Industry (pp. 61-73). Springer, Cham.