Uses of Big Data in Business Organizations Assignment

Uses of Big Data in Business
Organizations
Assignment 2: Research Methodology
Student Name: Student ID:
Unit Name: Unit ID: HI6008
Date Due: Professor Name:
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Executive Summary
Developing a research methodological framework is critical in order to conduct any study. In
order to conduct data analysis relative to Big Data, an appropriate research method has to be
selected and incorporated. Selecting an appropriate procedure will allow arriving at appropriate
conclusion related to the study. The analysis here pertains to research methods that have been
adopted for the purpose of this study.
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Table of Contents
Executive Summary.........................................................................................................................2
1.0 Introduction................................................................................................................................4
2.0 Project Objective.......................................................................................................................4
3.0 Project Scope.............................................................................................................................4
4.0 Literature Review......................................................................................................................5
5.0 Research Questions/ Hypothesis................................................................................................8
6.0 Research Methodology..............................................................................................................9
7.0 Research Limitations...............................................................................................................15
8.0 Time Schedule (Research Plan)...............................................................................................15
9.0 Conclusion...............................................................................................................................15
10.0 Reference List........................................................................................................................16
11.0 Appendix................................................................................................................................18
11.1 Appendix 1.........................................................................................................................18
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1.0 Introduction
Big Data presents a number of complicated challenges with advantages in today’s business
environment (Wu et al., 2014). In the last examination of literature analysis relating to Big Data
several advantages with disadvantages was arrived at. The scope related to this analysis includes
a brief description of several research methods that has been utilized for the study. Research
methods have incorporated ways and techniques that have been used for the study include data
collection and analysis for the same.
2.0 Project Objective
Some of the project objects for the current project are as follows;
 Project Objective 1: To be able to identify research philosophy and approach
 Project Objective 2: To evaluate the research design and research tools to be used for
the study
 Project Objective 3: To understand the data collection and analysis techniques for the
same Project Objective 4: To understand the limitations and ethical consideration for the
study
 Project Objective 5: To understand the timeline in which the project is to be completed
3.0 Project Scope
Big Data has turned out to be one of the main patterns that influence organization's execution
inside the business. The term is for the most part used to allude to extensive volumes of
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informational collections that are differing and complex in nature on a monstrous scale.
Partnerships influence utilization of such a lot of voluminous information with a specific end
goal to touch base at different complex vital choices (Zikopoulos & Eaton, 2011). Enterprises
gather and break down such voluminous measures of data with the end goal that they can have
suitable understanding in regards to the market and the different elements identified with it. Big
Data has discovered its application crosswise over enterprises as well as additions pertinence in
medicinal services and other non-benefit arranged exercises. Because of its tremendous ability to
suit huge voluminous and complex information associations think that it’s powerful to get to the
same and after that utilization it crosswise over different offices. From the above discourse it can
be examined that Big Data has a few pertinence subsequently the extent of this examination
investigations the few employments of the same in associations.
4.0 Literature Review
Big Data has a few prominent definitions that have been produced by enterprises and analysts in
the area. Big Data has been reforming ways and means by which data was before utilized when
contrasted with date. Big Data suggests a generous bit of unrefined data that is accumulated,
secured and separated through various means which can be utilized by relationship to grow their
capability and take better decisions. The improvement of Big Data is an immensely positive for
society in all viewpoints (Wang et al., 2014). The other request displayed negative inclination,
including the working of the Internet, human and machine examination of Big Data will cause
more issues. Such information can either be composed and unstructured structures. Sorted out
Data is more adequately separated and created into the database.
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Accentuates on the need of investigating Big Data for understanding their adequacy inside
partnerships. Such information can't be easily deciphered by standard data models and
techniques. In fact, a regularly expanding number of associations have been using Big Data and
related examination approaches as a way to deal with procure information to better help their
association and serve their customers, benefitting from the advantages of enormous information.
The usage of Big Data is getting the opportunity to be typical these days by the associations to
outmaneuver their friends. In numerous endeavors, existing contenders and new candidates alike
will use the frameworks occurring in light of the separated data to fight, create and achieve mark
faithfulness. By joining extraordinary, checked sources, more associations can make
significantly exact learning sources. Half of senior authorities report that getting to the right data
is troublesome. New investigation ought to be bought and used. In addition examination of Big
Data will be mishandled by successful people and foundations with self-absorbed inspiration that
control revelations to advance the guard for what they require.
While unstructured Data, is essentially harder to analyze as it uses a grouping of game plans. The
noteworthiness of Big Data does not turn around amount of much data an association has yet
how an association utilizes the accumulated data. The association can take data from any source
and explore it to find answers which will make upper hands for it. With the way toward
separating Big Data an association can hint at change cognizance of current monetary
circumstances. By this, it can progress past its opponents. Big Data examination can do
conclusion examination. Along these lines, an association can get feedback about who is stating
what concerning an association. Big Data makes the affiliations make new improvement
openings and out and out new classes of associations that can unite and dismember industry data.
These associations have adequate information about the things and organizations, buyers and
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suppliers, customer slants that can be gotten and dismembered. It furthermore appreciates and
enhances business shapes. Associations that arrangement with items can streamline their stock in
perspective of farsighted models delivered from the internet organizing data, web look examples
and atmosphere guesses. Irregularly, every one of the structures would support and joins the data
into a database where reports could be run and everyone could comprehend into what was
occurring.
The issue was that the database development basically was not capable manage various, diligent
contribution of data. It was additionally not ready to change the moving toward data logically.
Better business decisions suggest that associations can reduce the threat of their decisions, and
settle on better decisions that decline costs and addition publicizing and arrangements adequacy.
With Persistent Big Data examination an association can stay one phase before the restriction or
get prompted the moment and association or its quick adversary is changing philosophy or
cutting down its expenses for example (Chen, Mao & Liu, 2014). However Big Data will be
negative for society about in all respects. There may be issues identified with security and
manhandle and unapproved singular information. Regardless, looking positive slant, there are
incredibly interesting use cases of Big Data, which perceives tremendous measures of data cases
of affiliations and interdependencies.
Something as essential as filtering customers from an association or web examination can give
an immense measure of learning into an association in acquirement processes. The cash related
world is to a great degree appealing for wrongdoers. With a consistent secure system, attempts to
hack into an association affiliation are prompted immediately. Distortion can be recognized the
moment it happens and suitable measures can be taken to limit the damage. Using constant bits
of learning requires a substitute technique for working in the event that the association routinely
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just gets encounters once every week, which is to a great degree fundamental in an impressive
measure of affiliations, tolerating these bits of information reliably will require a substitute
approach and strategy for working. Bits of learning require action and instead of following up on
seven days after week commence this action are at present consistently required. Consistent
learning into bungles causes associations react quickly to mitigate the effects of an operational
issue. This can save the action from falling behind or tumbling absolutely or it can save
association customers from halting using an association things. Speedier decisions can be put
aside a couple of minutes examination that better suit the (present) customer.
5.0 Research Questions/ Hypothesis
In order to attain research goals and objectives, the following research questions needs to be
attained.
-Primary Question: What are the scopes of Big Data in international business framework?
-Secondary Questions: 1. What are the advantages and disadvantages related to Big Data?
2. How can data be collected related to Big Data application in the industry?
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6.0 Research Methodology
While conducting any study, the research methodology acts as one of the most vital features and
hence it requires significant attention (Lewis, 2015). Hereby, a thorough sketch of the research
methodology adopted by a scholar to complete the study while obtaining solutions for the
problems of research has been studied. At first the chapter introduces various facets of the
research methodology followed by giving proper justification regarding the adoption of the
viable methods to accomplish the study.
Research Philosophy
While laying the foundation of aspects, the research philosophy determines the comprehensive
structure of the study. Axiology, Epistemology, Ontology and Rhetoric are the four research
philosophies from which a scholar has the liberty to choose any according to his need (Maxwell,
2012). When the scholar adopts ethics and aesthetics as the most vital variables of a study,
Axiology Research Philosophy is used. When the main object of any study is to defragment
disposition and the sequence of any specifics on the proper area, the Epistemology Research
Philosophy is resorted. However when the primary objective of the scholar is to create replica of
reliable state of affairs and individual understanding about pragmatism, the Ontology Research
Philosophy is the best option. The Rhetoric Research Philosophy, on the other hand is adopted in
those studies where the main aim lies in the fact of minute inspection of any possible problems
followed by exploration of the correlated features to interpret the results for formulating
judgments. Here the scholar will adopt epistemology research philosophy.
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Approach to the Research
A part of the research approach is formulated by the adoption of Inductive or Deductive
Approach and/or Qualitative or Quantitative Approach.
Qualitative and Quantitative Approach
In Qualitative Research Approach, with the help of subjective approach, a reminiscent
examination is undertaken to obtain the explanation to issues which are under study. The
Quantitative Approach on the other hand is based upon usage of numbers to be analyzed with
mathematical and/or statistical tools. Qualitative data related to the study will be collected for
the study.
Inductive or Deductive research approach
In the Inductive Study, observations are pursued first, then they are studied and finally the results
are obtained leading to the formulation of theories. The Deductive Study however relies on the
application of theories to infer results. For this particular study deductive techniques will be
adopted.
Research Design
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Among the most crucial components in Research Methodology is the Research Design because
the functionality and efficiency of the methodology is determined by this and an operational
research process is established.
Types of Research design
Explanatory, Exploratory, Predictive and Descriptive Designs are the four types of Research
Design that a researcher can choose accordingly. When the researcher decides to settle on the
fundamental associations which are shared by variables under study, Explanatory Design is
deployed (Taylor, Bogdan & DeVault, 2015). In case of informational deficiency the exploratory
study is adopted by the researcher to design concrete solution by exploring various information
from different sources. Where the explanatory research results are interpreted for predicting
upcoming occurrences, predictive Research Design is pursued. The descriptive research design
on the other hand is undertaken for the studies where detailed descriptions for specific
occurrences are involved. For the scope of this study, exploratory research design will be
adopted.
Research Method
For collecting information from primary sources to support research design and accomplish
research objectives, the tools of Research Methods are adopted by scholar.
Research Tools
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Observation: Structured and Participative Observations
In case of qualitative studies, the Structured Observations are adopted where according to the
predefined segments; analytical record is made of the observations of the researcher. In case of
Quantitative Studies, Participative Observations are adopted where the scholar participates in
real setup with other sample participants and interprets information according to the personal
experiences.
Interviews: Structured interviews and semi-structured
Structured and Semi-structured interviews are two types of interviews and the scholar can adopt
any of the two types of personal interviews accordingly (Mitchell & Jolley, 2012). The
Structured Interview is such a personal interview where the flexibility of the interviewee is
reduced as the code of conduct is set according to the predefined code determined by the
interviewer. The Semi-structured Interviews are flexible personal interviews where neither the
interviewer nor the interviewee is fully controlled for the conversation, rather are guided by the
few sets of predefined code of conduct.
Questionnaires:
Open-ended and Close-ended Questionnaires –a researcher can opt for any of the two according
to the study type and research aims (Wahyuni, 2012). No restriction is imposed on the
respondents in case of Open-minded Questionnaires as here they have liberty to express
opinions. However in case of Close-ended Questionnaire, the sample respondent is provided a
set of questions with predefined choice of options from where the respondent can choose
accordingly.
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Focus groups:
Here the researcher chooses a specified number of people and forms a group to pursue discussion
on the given problem topic. The research scholar takes note of individual perspectives of the
group members during the discussion and thereby, interprets result.
Sampling and Related Techniques
A proper depiction of an entire population is considered as sample and the selection of sample is
called sampling (Christensen et al, 2011). It is basically not viable to record the opinions of the
individuals within a population; hence the sample size is chosen to conduct a research.
Extrapolation of the results obtained from the sample has resemblance with the opinions of the
population. The researcher has the liberty to choose the procedures of probability and non-
probability sampling.
Methods of Data Collection
Generally, data is collected from primary and secondary sources. The unadulterated data or the
primary data is collected originally to meet specific under-observation research requirements
while the secondary data consists of the information which is published already (Meyers, Gamst
& Guarino, 2016). The Primary Data was obtained from two sets of respondents namely the
managers and employees of the companies that make use of Big Data. Randomly some of the
employees of the companies were approached physically in their offices and were requested to
take part in the surveys. Questionnaires were provided to them once they agreed and information
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was collected. To approach all the employees physically was impossible, so their email ids were
obtained from their offices and afterwards they were sent emails with attached questionnaires.
They were requested to take part by filling the questionnaires up and respond over the same
medium (Saunders & Lewis, 2012). In case of Interviews with the managers, appointments were
availed by approaching physically and then they were met on the scheduled time.
Secondary data was gathered from variegated sources like books, journals, articles, newsletters,
newspapers, government periodicals, internet publications, and magazines and so on.
Data Analysis Methods
Frequency Analysis with other mathematical and statistical tools were used to analyze the
quantitative data availed from questionnaires (Tufford & Newman, 2012). Data was recorded
and analyzed with MsExcelToolpack. Qualitative data obtained from interview schedules were
analyzed descriptively.
Ethical considerations
1. No adulteration of information was done in any form
2. Reassurance of seclusion, secrecy and inscrutability was given to respondents with
information security
3. Respondents were not forced in any way and they participated in free will and free
consent.
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4. To attain lucidity in communication, the aim, scope and purpose of the research study
was explained to the respondents.
5. The scholar too assured of not being bias in any way.
7.0 Research Limitations
The limitation of the study lies in the fact that very small size of sample in comparison with the
population size was used in the research. It is because the fact that a sample cannot be a proper
representative of the entire population.
8.0 Time Schedule (Research Plan)
A research plan needs to be developed for the purpose of accomplishment of the entire study.
The current scope of the study has made use of Gantt chart for the procedure. Appendix 1
9.0 Conclusion
The proposed research methodology is aimed at attending the research goals. An extensive
research methodological framework has been suggested that will allow accomplishment of Big
Data collection and analysis thereafter for the project.
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10.0 Reference List
Chen, M., Mao, S. and Liu, Y., 2014. Big data: A survey. Mobile networks and
applications, 19(2), pp.171-209.
Christensen, L.B., Johnson, B., Turner, L.A. and Christensen, L.B., 2011. Research methods,
design, and analysis.
Lewis, S., 2015. Qualitative inquiry and research design: Choosing among five
approaches. Health promotion practice, 16(4), pp.473-475.
Maxwell, J.A., 2012. Qualitative research design: An interactive approach (Vol. 41). Sage
publications.
Meyers, L.S., Gamst, G. and Guarino, A.J., 2016. Applied multivariate research: Design and
interpretation. Sage publications.
Mitchell, M.L. and Jolley, J.M., 2012. Research design explained. Cengage Learning.
Saunders, M.N. and Lewis, P., 2012. Doing research in business & management: An essential
guide to planning your project. Pearson.
Taylor, S.J., Bogdan, R. and DeVault, M., 2015. Introduction to qualitative research methods: A
guidebook and resource. John Wiley & Sons.
Tufford, L. and Newman, P., 2012. Bracketing in qualitative research. Qualitative social
work, 11(1), pp.80-96.
Wahyuni, D., 2012. The research design maze: Understanding paradigms, cases, methods and
methodologies.
Wang, L., Zhan, J., Luo, C., Zhu, Y., Yang, Q., He, Y., Gao, W., Jia, Z., Shi, Y., Zhang, S. and
Zheng, C., 2014, February. Bigdatabench: A big data benchmark suite from internet services.
In High Performance Computer Architecture (HPCA), 2014 IEEE 20th International Symposium
on (pp. 488-499). IEEE.
Wu, X., Zhu, X., Wu, G.Q. and Ding, W., 2014. Data mining with big data. IEEE transactions
on knowledge and data engineering, 26(1), pp.97-107.
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Zikopoulos, P. and Eaton, C., 2011. Understanding big data: Analytics for enterprise class
hadoop and streaming data. McGraw-Hill Osborne Media.
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11.0 Appendix
11.1 Appendix 1
GANTT
CHART
Business Research
Research Outcome
15
days
30
days
45
days
60
days
75
days
90
days
110
days
130
days
Research Introduction
Objectives & Research
Questions
Literature Review
Data Collection
Data Analysis
Discussion & Findings
Conclusion &
Recommendations
Reflection
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