COM3005: Research on Big Data Impact on Sainsbury's Consumers

This report explores the role of big data technology in enhancing consumer understanding within the retail sector, focusing on Sainsbury's. It begins by outlining the research process, including the aim, objectives, research questions, and rationale behind studying big data's impact on Sainsbury's consumers and society. The report differentiates between types of data, emphasizing the importance of big data and how it contrasts with conventional data storage. It discusses methods for collecting and evaluating data sources, highlighting the significance of primary and secondary data in marketing decision-making. The analysis delves into information security systems, the potential for data compromise, and the use of data in monitoring and measuring organizational performance, particularly in relation to data transformation error rates and dark data. The research proposal outlines the study's methodology, including research type, data collection, and data analysis techniques. Ultimately, the report aims to evaluate the concept and impact of big data implementation on Sainsbury's consumers, providing a case study analysis.

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
better understanding of the consumers within the retail sector: A study 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 large amount of data that can
not be processed or stored by conventional data storage or even processing equipment.

Collecting data and evaluate sources
 Primary data are first-hand data collected by researcher himself. Whereas secondary
data are 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.