COM3005: Introducing Research Skills - Big Data and Consumer Behavior

This report, created for the COM3005 Introducing Research Skills module, investigates the application and impact of big data within the retail sector, specifically focusing on Sainsbury's. The research explores the research process, aim, objectives, research questions, and rationale behind analyzing big data in understanding consumers. It examines data collection methods, including primary and secondary data, and evaluates academic sources for relevance and credibility. The report delves into data analysis, information security systems, and the use of data in monitoring and measuring performance. It concludes with a research proposal and references, offering a comprehensive overview of big data's influence on consumer behavior and marketing decisions within the retail industry. The report highlights the importance of data in making marketing decisions and provides an analysis of the impact of big data on consumers of Sainsbury's.

COM3005 INTRODUCING
RESEARCH SKILLS

TABLE OF CONTENTS
RESEARCH INTRODUCTION
TASK 1
Research process
Aim
Objectives
Research questions
Rationale
Types of data
TASK - 2
Collecting data and evaluate sources
Importance of data in marketing decision – making
Academic sources- Relevance and Credibility-
TASK 3
Analysing and Interpretation-
TASK 4
Information security systems
Use of data in monitoring and measuring performance-
Feedback from lecturer
Research proposal
REFERENCES

RESEARCH INTRODUCTION
Research process
 The research topic of the particular research is big data
technology for a more precise and clear understanding of the
consumers within retail sector: An analysis on Sainsbury's.
 A research process is basically a procedure which includes
identification of the problem, reviewing the literature,
clarification of the issue, clarification of the terms and the
concepts that are being used, development of the plan, collection
of data, analysis of data, etc.

Aim
 To analyse the role of big data and its impact on the understanding of the consumers in Sainsbury retail
store.
Objectives
 To evaluate the concept of big data.
 To examine its impact of big data on society.
 To analyse the impact of big data on consumers of Sainsbury.
 To recommend ways through which big data can be implemented within organization.

Research questions
 What is the meaning of big data?
 How does big data impact the society?
 How does big data impact the consumers of Sainsbury?

Rationale
 Big data is very essential for the working of every organization in the present
times. This topic is chosen for the sole purpose of understanding the impact that
implementation of big data has over the consumers of Sainsbury and the society
overall.

Types of data
 A brief about information, knowledge and data differ
 Data are raw in nature, it can be figures or facts or even information that is usually
stored as well as used by researcher.
 Big data
 It is popular term recently, it has come to define huge variety of diverse
information which is not processed and stored by the conventional ways of data storage
or even the equipment.

Collecting data and evaluate sources
 The Primary data is the raw data collected by researcher himself. Whereas the
secondary data is collected by someone else earlier.
Types of method used in research
 For this research, we use primary research that is methodology used by the researchers
to gather data directly, instead of depending on data directly.

Collect data
Importance of data in marketing decision – making
 There are various data like the browsing patterns of the consumers, the social media
activities, their online behaviour helps in building and enhancing the marketing efforts
at the workplace.
Academic sources- Relevance and Credibility-
 Akhtar, P., and et.al., 2019. Big data‐savvy teams’ skills, big data‐driven actions and
business performance. British Journal of Management, 30(2), pp.252-271.

Analysing and Interpretation-
 The most reliable and most of the data has been collected from the second resource.

Information security systems
 Compromising of data can be done through various ways. It basically refers to
misusing or loosing of the essential and important data that is given by the customers to
the company.
Use of data in monitoring and measuring performance-
 Collecting data for the different services allows companies in measuring performance
of the organization.

Data transformation error rates-
The process that takes in the one format and converts into the another formate are often the sign that
the data quality has certain problems. These problems lead in the failure of the operations and this
helps in gaining the insight into the overall quality of the data.
Amount dark data-
It is data that can not use effectively because of data quality issue. So darker data can give more
problems in quality data.
Data time to value-
Calculate how long it takes team to derive result from given data set. While numbers of factors
affects data time to value.