IT 1: Data Science Application Areas Research Question Analysis

This assignment addresses the research question: "What application areas do users apply data science to?" The research explores data science as an IT technology for managing large datasets and making informed decisions. It emphasizes the importance of understanding data science applications in a rapidly evolving technological landscape, highlighting gaps in existing research and the need to examine data science's impact on business performance. The research employs both primary and secondary data collection methods, including a survey with 20 participants and a systematic literature review. Data analysis will be performed using statistical analysis techniques and Excel software. The assignment aligns with the course material by focusing on a computer science topic and applying relevant research methods, referencing previous studies and providing in-depth analysis of data science and its applications.

IT 1
What is your research question?
Data science is a kind of information technology that
provides a way to manage larger data sets effectively and
helps companies to obtain effective decisions from
gathering information. The selected research question
“what application areas do users apply data science too?"
This research question will be addressed in this
investigation by using effective data collection techniques
and data analysis processes.
Why do you think this question is important?
In this, generation the uses of computing devices and IT
networks are growing quickly that helps companies to
manage business performance effectively. Data science is
an advanced IT technology that provides a way to analyze
larger datasets in an appropriate manner. It is significant to
examine the importance of data science networks and
various applications where companies use data science
systems. This research will help to enhance skills in the
area of data science and manage research gaps that
occurred in recent studies. There is no specific research that
highlights the role of data science in companies and
applications of data sciences where users utilize data
science-based networks. For managing larger datasets and
performing data mining processes, data science techniques
can be adopted and this research will help communities to
evaluate the impact of data science on business
performance. Therefore, enhancing skills and examining
application areas of data science this research is conducted
that also helps to describe the characteristics of data science
technology.
What does previous research tell you about your
question?
Hazen, et al., (2014) reported that data science is an
effective technology that has the capability to evaluate and
analyze the gathered datasets and provide effective
information that helps to develop appropriate decisions in
the companies [1]. In terms of effectiveness, data science is
more reliable and efficient that can be adopted in the
companies to perform data mining processes. Venugopal,
Buyya and Winton, (2012) agreed on this point and
determined that there are numerous application areas where
users can utilize data science networks including fraud and
risk detection, internet search, website recommendations,
healthcare, data mining and analysis, airline route planning,
automated control systems, gaming and many more [2].
In which fraud and risk detection is a major application of
data science where companies can utilize data science-
based systems for determining and detecting the fraud cases
and malware signals effectively which can lead security
and privacy of data effectively [6]. Van, (2016) determined
that in healthcare sectors, data science technology helps to
evaluate and review the data of patients and implement
effective decision making approaches [3]. The previous
studies provided brief information about applications of
data science networks that produced gaps in the
investigation but this paper will describe each and every
point of data science and provide depth information in
regards to the applications of data science networks.
Provost and Fawcett, (2013) conducted a literature search
and determined that in healthcare, data science technology
is used to analyze medical images, perform drug
development operations, virtual assistance for consumers
and patients in order to provide supports and many more
[4]. Using, data science technology, business communities
can enhance organizational performance and increase
targeted advertising in an appropriate manner. Therefore, it
is reported that the utilization of data science technology is
beneficial for the companies and previous investigations
determined and evaluated the benefits and challenges of
What application areas do users apply to data science too?

IT 2
integrating data science in the business communities [5].
Moreover, the recent studies included theoretical and less
effective information in regards to data science but this
paper will help to provide depth analysis of data science
technology by which the research question will be
addressed effectively.
What data will you need to answer the question?
Data collection is a major section of the research that helps
to address research questions and enhance research quality
effectively. In this research, the primary and secondary data
will be gathered for addressing research concerns. The
primary data provide fresh information in regards to the
investigation topic while secondary data deliver theoretical
information that helps to address research problems. In this
paper, primary data will be gathered using a survey through
a questionnaire where the participants will provide their
viewpoints about data science technology.
On the opposite side, secondary data will be obtained by
conducting a systematic literature search that will deliver
theoretical information related to data science. Numerous
resources will be included for gathering information
including peer-reviewed papers, books, online websites and
many more. Moreover, a total of 20 participants will be
included while conducting a close-ended survey that will
help to provide reliable and appropriate information about
data science technology. Therefore, it is reported that using
such methods the researcher will be capable to obtain
effective information about data science and address
research concerns in an effective manner.
How are you going to analyses this data?
It is reported that data analysis is an effective section of the
investigation that has the capability to deliver appropriate
points and findings in the investigations. The utilization of
data analysis supports the writers to achieve research aims
and conclude effective points. Numerous kinds of methods
and techniques involved in the investigation such as content
analysis, statistical analysis, Excel, SPSS and many more.
In this investigation, the statistical analysis technique will
be adopted due to their ability to provide significant
findings and results in the investigation.
The utilization of such a methodology will help to evaluate
and gather both theoretical and numerical facts related to
data science technology. Moreover, Excel software will be
added for analyzing data which will help to evaluate
viewpoints of the participants in an effective manner and
represent data into graphical forms that can lead the
performance and effectiveness of the investigation. Content
analysis will not be used due to their less effectiveness
towards the primary data so; the statistical analysis
methodology will be adopted for analyzing the obtained
information from the literature review and survey through a
questionnaire. Therefore, using such methods the research
will be completed in less time and developed research
questions will be addressed in an appropriate manner.
How does this relate to the course material?
This course is related to the research where the students
require selecting a topic related to computer science and
providing effective information. Data science is a branch of
computer science that uses computing networks and
devices for evaluating and handling data of the companies
effectively. the chosen topic is related to the course
material and follows the provided guidelines where a
research question require to be developed. The chosen
methods and techniques are obtained from the course
material that helped to complete the research in a reliable
manner. So, it is reported that this research is related to the
course material.
References
[1]. B.T., Hazen, C.A., Boone, J.D. Ezell and, L.A.,
Jones-Farmer, “Data quality for data science,
predictive analytics, and big data in supply chain
management: An introduction to the problem and
suggestions for research and applications,”
International Journal of Production
Economics, vol. 154, no. 6, pp.72-80, 2014.

IT 3
[2]. S., Venugopal, R. Buyya and, L., Winton, “A
grid service broker for scheduling e‐science
applications on global data grids,” Concurrency
and Computation: Practice and Experience, vol.
18, no. 6, pp.685-699, 2012.
[3]. W., Van Der Aalst, “Data science in action,”
In Process mining, vol. 12, no. 6, pp. 3-23, 2016.
[4]. F. Provost and, T., Fawcett, “Data science and its
relationship to big data and data-driven decision
making,” Big data, vol. 1, no. 1, pp.51-59, 2013.
[5]. M.A. Waller and, S.E., Fawcett, “Data science,
predictive analytics, and big data: a revolution
that will transform supply chain design and
management,” Journal of Business Logistics, vol.
34, no. 2, pp.77-84, 2013.
[6]. D., Donoho, “50 years of data science,” Journal
of Computational and Graphical Statistics, vol.
26, no. 4, pp.745-766, 2017.