MG413 Data Insights: Research Methods and Data Analysis Presentation

This presentation delves into the crucial role of data insights in modern business studies, focusing on both quantitative and qualitative research methodologies. It begins by outlining the functions of quantitative research, emphasizing questionnaire design and its application in marketing research and data analysis. The presentation then explores qualitative research, focusing on discussion guide design and its use in gathering non-statistical data to enhance decision-making. It explains correlation and regression, illustrating how these techniques are utilized to analyze relationships between variables. The presentation also covers time series analysis, a method for tracking data trends over time. Furthermore, it addresses how data can be gathered and utilized to inform business decisions, highlighting the importance of both quantitative and qualitative methods in enhancing decision-making processes. The presentation concludes by emphasizing the significance of these research methods in providing a comprehensive understanding of collected data and improving business outcomes. It also highlights the use of client information to understand and respond to their needs. The presentation also discusses the critique of problems surrounding the analysis techniques.

Data insights

Table of Content
Introduction
The functions of quantitative research in modern marketing research
and data analysis.
The functions of qualitative research in modern marketing research
and data analysis.
Correlation and regression and how it is utilized
Time series
How data can be gathered & utilized to make informed business
decisions.
Conclusion
Reference

INTRODUCTION
 The main purpose of this report is to understand the
several objectives of data research procedures in a
advance business.
 There are two type of research methods are analyzed
which are qualitative research and quantitative
research.
 This report include various types of qualitative and
quantitative research methods along with its
importance.

The functions of quantitative research in
modern marketing research and data
analysis
 Qualitative marketing study is a method of asking structured
inquiries to an intended population via interviews, elections,
or quizzes. Comments can be evaluated to generate good
choices about the things which can enhance goods and
operations, leading in greater rates of participant engagement.
 Whenever a substantial data which is illustrated representing
a wide range of things is assessed, findings can be obtained
which can prove beneficial in the long run.

Questionnaire

The functions of qualitative research in
modern marketing research and data
analysis
 In an of the topic or to create in assessment
investigation, non-statistical data is gathered
and evaluated so as to improve overall thought
process or events.
 It can be employed so as to have a
comprehension vocative researching topics.

Continue…
 This presentation, for example, can be employed to
evaluate fresh advertising ideas or goods and give a
comprehensive image of how prospects or users respond to
them.
 It could also be employed to identify non-quantitative
perceptions or emotions. Whenever a customer or user
views a commercial or item package, the behavioural
response, nonverbal cues, or vocal modulation is
evaluated.

Questionnaire

Correlation and regression and how
it is utilized
 Correlation: The correlations is a quantitative measure
which quantifies how precisely two elements are
directly related, and it's a prevalent technique for giving
direct links with aspects and consequence relations.
 Whenever single database contains differs, regression
analysis evaluates the link among the two information
groups and the alteration in another variable item.
 Uses: Correlation is used to analyze the capability and
direction of liner relationship among two or more than
two variables. It is used to notice the multiplicity of the
inter related variables.

Continue…
 This data could be used to enhance the customer
experiences. Several firms could use client
information to further comprehend and respond to
their clients' demands.
 By observing client behaviour and different ideas
and evaluations, businesses can adjust their online
appearance, products, and solutions to match the
specific marketplace. Businesses that collect
information in a variety of methods from a wide
range of resources.

Time series
 A temporal sequence is a group of information objects
which occur in sequential sequence across a period of
duration. A trend analysis in marketing, for instance, tracks
the flow of particular set of data via duration, like the
stock prices, with sequential evaluated aspects collected.
 Investments in following the value of a securities through
duration, for instance, is extremely common.

Continue…
 It is being employed to identify the impacting factors and
basic mechanism of observational reality, as well as to
choose a predicted framework and take smarter choices.
 A moment cycle is a collection of variables which appear
in a specific arrangement throughout moment. A moment
succession in investment follows the flow of selected
observations, including the value of an asset, more than a
specific length span with information units collected at
frequent durations.

Critique of problems surrounding the
analysis techniques:
 The explanations and outcomes of the
elements must have no effect on the
regression issue. Since this presumption is
really not right, applying the regression
model to estimate the levels of a factor might
yield to incorrect and deceptive conclusions.
 Correlation could not be applied to infer
causative links among data that are assessed.

Conclusion
The investigation of qualitative and quantitative techniques
plays vital role in modern business studies. There techniques
provide better understanding about the collected data.
Qualitative techniques provide in-depth knowledge about
specific data on the other hand quantitative data provide
accurate data and results. Both the techniques help to
enhance the business decision making of a organization.

Reference
 Bathla, G., Rani, R. and Aggarwal, H., 2018. Comparative
study of NoSQL databases for big data
storage. International Journal of Engineering &
Technology, 7(2.6), pp.83-87.
 Dai, H.N., Wang, H., Xu, G. and Imran, M., 2020. Big data
analytics for manufacturing internet of things:
opportunities, challenges and enabling
technologies. Enterprise Information Systems, 14(9-10),
pp.1279-1303.