Data Insights And Collection Process Assignment sample

Data Insights And Collection Process Assignment

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Introduction of Data Insights And Collection Process Assignment

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  • Data collection is s significant process for developing the research work.
  • Effective data determines the success and effectiveness of the study. 
  • The data collection and analysis process depends on the research topic.

Data collection allows the research to increase decision-making. Identify the problems and guides to develop the accuracy of the theory. 

Quantitative research in marketing and data analysis 

  • Quantitative research refers to a systemic investigation to gather quantifiable data (Christou and Chatzigeorgiou, 2020). 
  • It is mainly performed with computational, statistical and numerical techniques. 
  • Quantitative research sends out different processes like surveys, interviews, and questionnaires. 

In order to conduct quantitative research, several distinctive tools are required such as determining the sample size, prior studies, generalizations of results as well as close and open-ended questioners (Christou and Chatzigeorgiou, 2020). Quantitative research is very effective to collect accurate data quickly. There is a great opportunity to analyse data properly eliminating bias. 

Quantitative research in marketing and data analysis 

  • Questionnaires are an instrument that consists of a series of questions to gather data from respondents (Hussain et al. 2020). 
  • It can be done through offline as well as online terms. 
  • It is a relatively cheaper, quicker and more efficient data collection process (Benoit et al. 2018). 

Questionnaires guide to getting data that are more reliable from a large sample size very easily. The making of questions should be effective to collect all the necessary information about the research topic. 

Qualitative research in marketing research and data analysis

  • Qualitative research emphasizes gathering information through traditional communication. 
  • Open-ended communication guides to collect qualitative data. 
  • This process is based on the strict disciplines of social sciences (Benoit et al. 2018). 

Qualitative research can be conducted through a record-keeping process as well as proper chase study follow-up techniques. In order to develop an innovative product as well as generate new ideas, qualitative research is conducted. 

Qualitative research in marketing research and data analysis

  • Discussion guide design helps in conducting interviews during research.
  • The timing plan is the main component of the discussion guide design (Li, 2021).
  • The best discussion guide design depends on the choice of questions and sample. 

The discussion guide design guides the research developers to fluently conduct the interview session that guides to increase the efficiency of the study (Wulandari, 2020). Following the simple structure and maintaining the time the discussion guide design can be developed.

Application of the correlations and regression in research work

  • Correlation is a quantifying research tool to make a balance between two variables.
  • Regression describes the process of how the independent variables are connected with dependent variables (Wulandari, 2020). 
  • These two research tools are used to collect the relationship values of variables of a research topic.

These two reaserrch tools are mainly used in the data analysis process for evaluating the values of the independent as well as dependent variables. The connection between variables of the research topic is also calculated with the application of correlation and regression tests. It is seen that the correlation and regression test can increase reliability and validity by more than 45% (Chatterjee, 2021). Two different types of correlation are mainly seen as positive and negative.

Application of the time series in research work

  • Time series analysis is the mathematical methodology that proposed a potential time series for the research. 
  • It is also viewed in all types of longitudinal designs for research (Kafle, 2019). 
  • The time series is mainly applicable for the measurement of the research duration. 

The time series can also create several research problems in terms of primary research as conducting primary reaserrch is very difficult for the accumulation of data collection process.

Critical analysis of correlations, regression and time series in data analysis

  • Correlation test guides to improve the decision making process for business activities (Kafle, 2019). 
  • Regression test guides to evaluate the values of bug data in terms of business activities.
  • The correlation and regression values guide to improving more than 24% of business productivity by evaluating effective business decisions (Lim and Zohren, 2021). 

In order to analyse the financial data of the organization correlations, regression and time series is very significant. Time series improves the time management skills for the business product development.

Data collection and business decision 

  • Data collection process makes a high standard for the global business style. 
  • Data-driven decisions help to increase business productivity as well as profit by evaluating the collected data (Ismail Fawaz et al. 2019). 

Proper data collection guides to improve of the business decision that leads to the success of the business. The data collection process guides in determining the proper strategic approach to the business.


  • The primary and secondary methods of data collection are mainly conducted during research.
  • Data collection methods empower to create informed business decisions.
  • Accurate data collection guides to back up the business arguments. 

The data collection process increases the reliability and validity of the research paper to the learners and future researchers.



Benoit, K., Watanabe, K., Wang, H., Nulty, P., Obeng, A., Müller, S. and Matsuo, A., 2018. quanteda: An R package for the quantitative analysis of textual data. Journal of Open Source Software3(30), p.774. 

Chatterjee, S., 2021. A new coefficient of correlation. Journal of the American Statistical Association116(536), pp.2009-2022.

Christou, E. and Chatzigeorgiou, C., 2020. Adoption of social media as distribution channels in tourism marketing: A qualitative analysis of consumers’ experiences. Journal of Tourism, Heritage & Services Marketing (JTHSM)6(1), pp.25-32.

Hussain, S., Jamwal, P.K., Munir, M.T. and Zuyeva, A., 2020. A quasi-qualitative analysis of flipped classroom implementation in an engineering course: from theory to practice. International Journal of Educational Technology in Higher Education17(1), pp.1-19.

Ismail Fawaz, H., Forestier, G., Weber, J., Idoumghar, L. and Muller, P.A., 2019. Deep learning for time series classification: a review. Data mining and knowledge discovery33(4), pp.917-963.

Kafle, S.C., 2019. Correlation and regression analysis using SPSS. OCEM Journal of Management, Technology & Social Sciences, pp.126-132.

Li, B., 2021, April. Quantitative Analysis of Salary Data in the Big Data Era. In Journal of Physics: Conference Series (Vol. 1881, No. 3, p. 032022). IOP Publishing.

Lim, B. and Zohren, S., 2021. Time-series forecasting with deep learning: a survey. Philosophical Transactions of the Royal Society A379(2194), p.20200209. 

Peñarrubia-Lozano, C., Segura-Berges, M., Lizalde-Gil, M. and Bustamante, J.C., 2021. A qualitative analysis of implementing e-learning during the COVID-19 lockdown. Sustainability13(6), p.3317. (Peñarrubia-Lozano et al. 2021)

Wulandari, L.K., 2020. Optimasi Komposisi Tipe Rumah Dengan Program Qm (Quantitative Analysis For Management) Untuk Menentukan Studi Kelayakan Perumahan Kitanara Regency Jombang. INFOMANPRO9(2), pp.40-43.


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