Data Insight: Quantitative, Qualitative, and Time Series Analysis

This presentation provides an overview of data insight and its significance in business decision-making. It begins by defining data insight as the knowledge gained through analyzing information to facilitate effective business strategies. The presentation explores the roles of both quantitative and qualitative research methods in modern marketing, detailing how these methods are used to collect and analyze data through surveys, questionnaires, and statistical tools like regression and correlation. It also covers time series analysis, including data preparation, decomposition, modeling, and forecasting. Furthermore, the presentation critiques issues related to correlation, regression, and time series data, such as sampling problems in big data environments. It concludes by emphasizing the crucial role of data in informed business decisions and highlights methods of data collection, such as surveys and online tracking. The presentation underscores the importance of data insight for companies to analyze data and make effective, data-driven decisions.

DATA
INSIGHT

TABLE OF CONTENT
 Introduction
 Role of quantitative research
 Role of qualitative research
 Correlation and regression
 Time series
 Critique of issue
 Data collection
 Conclusion
 Reference

INTRODUCTION
 Data insight is being defined as the knowledge which
the company gains by analyzing the set of information
relating to any particular problem or situation.
 By analyzing these situations and information the
company takes effective decisions for the better
working of the company.

Role of quantitative research in
modern marketing research
 Quantitative market research is a type of technique wherein the researcher asks
questions to the target audience in form of survey or questionnaires or online
research.
 Further this collected data is being analyzed with help of the different statistical
tools like regression, correlation, ANOVA and many other different types of tools
and techniques (Kuznetsov, 2019).
 In the end the conclusions are drawn from the data analysis and then decisions are
taken what have to be done.

Role of qualitative research in modern
marketing research
 The qualitative research is the one under which the non- numeric information is
being used in order to solve the problem or the issue.
 The qualitative research plays an essential role within the effective modern
marketing research (Huebner and Moore, 2019).
 This is particularly because of the reason that this qualitative research is
subjective in nature as it does not involve the numeric facts and figures.
 Hence, this enhances the theoretical knowledge relating to the issue or the
problem.

Correlation and regression and how it
is used
For using correlation following steps are being followed-
 Data sample is obtained from X and Y variables.
 The mean of them is calculated and mean is subtracted from every value from both the series.
 Further every value is being multiplied with the value which came after subtracting mean and then sum
of the multiplication is done (this is value of numerator within the formula)
 After that square of a- value that is subtracted value is done and sum is taken.
 Further the square root of value obtained which is the denominator in the formula.

CONTINUED

CONTINUED
 Regression- this is a tool of data analysis which assist in analyzing the relationship
between an independent and dependent variable.

Time series and how it is used
Time series is defined as the any group of statistical information which is collected at regular
intervals of time (Time series analysis, 2021). This time series analysis is being used in order to detect the
changes within the pattern of the collected data.
 The first step in the time series analysis is data preparation
 The next step involves the time series decomposition
 Furthermore, the next step involves the use modelling
 In addition to this next step involves the forecasting of the data using the time series data gathered
and prepared.
 The last stage is of model evaluation wherein the model selected is being evaluated that is whether
the model is successful in reaching to the aim and objective of the study.

Critique of issues relating to time series,
correlation and regression
 There are many different types of issues which are being present in the use of correlation,
regression and time series data.
 This is particularly because of the reason that it might be possible that the use of these
tools might involve different types of problem and issues.
 The major issue is that there might be issue with the sampling.
 This is particularly because of the reason that when the research is of big data then it
becomes a little tough to select the sample as the data is very big.

Data collection and informed business
decision
 From the above analysis it is clear that data plays a crucial role within the effective
business decision making.
 This is particularly because of the reason that when the business has to take decision then
they will have to rely upon the relevant data and statistics.
 Different methods of collecting data are
 Survey
 Online tracking

CONCLUSION
In the end the presentation concluded that data insight is very important for
the company to analyse data for the purpose of taking effective decisions.
This is essential as the data provides an insight that how this data can be used
in order to manage the business and take effective decisions.
The above presentation included that correlation, regression and time series
are a good tool to analyse the data and take effective decision for the business.