Data Insights for Business Decisions - A Study on Sainsbury's

This report focuses on the impact of big data on decision making process of Sainsbury's, the second largest supermarket chain in UK. It covers the types of data used, difference between market orthodox and big data, ways of information storage, strategic importance of data and ways to improve data capture.

Data insights For Business
Decisions

Table of Contents
 Introduction:
 MAIN BODY
 Evaluation of type of data used and collected by the company:
 Description of difference between market orthodox and big data:
 Explaining about the ways in which the information is stored:
 Description of the impact of technological development on the use of data for decision making process:
 Analysing about the strategic importance of data in day to day operations of organisation:
 Evaluation of ways to improve data capture as well as usage in the firm:
 Conclusion
 References

Introduction
The term big data is termed as large volumes of data that can be in structured as well as unstructured way. The big
data supports the organisation to make facts and evidence based decision making process. The main purpose of big
data is to optimise business process by gaining an deep insight about the customers of company. For this report
Sainsbury's organisation is taken into consideration. The company is currently the second largest supermarket chain
based in London, UK. The report will cover about the types of data which is used by the company. In addition to this,
the report will highlight orthodox market research and will explain about how big data is different from this.

Evaluation of type of data used and collected
by the company
The big data is crucial for the modern companies as it supports the organisation to make well informed decisions as
well as also helps the firm to understand customer wants and desires in the most effective manner(Singh, 2019). The
use of big data assists the firm to analyse customer trends in the most appropriate manner which directly helps firm
to develop and implement fact based strategies in order to improve its competitive position in market. In context to
Sainsbury's firm, the second largest supermarket chain of UK undertake use of big data tools which helps the
organisation to effectively predict the future demands of the customers. The collection of data through machine
learning supports the company to efficiently know what products do customers want to buy in future.

Description of difference between market
orthodox and big data
The orthodox market research techniques is considered as the set of traditional techniques that leads the firm to
gather relevant information about the market trends. This old data collection method is used in order to better
understand the customer desires form which the business can analyse this data with the purpose of designing better
products and services. This market research method undertakes use of surveys, filling questionnaire as well as
personal interviews in order to extract accurate information about current market trends(Upadhyay and Kumar,
2020).

difference between market orthodox and big data
Basis Traditional market research Big data
Definition The orthodox market research
techniques is termed as method of
market research that supports the firm
to collect necessary information about
customers through practising
traditional way such as doing surveys
etc.
The big data is the modern type of
market research techniques which uses
machine learning as well as AI
technology while collecting relevant
data about current market trends.
Time taken The time taken to perform collection
of customer information is long as
well as tedious(Mishra and et.al.,
2018).
The time taken to collect customer
information through big data
techniques is very less as compared to
traditional methods of market
research.
Tools used The orthodox market research
techniques takes use of surveys,
personal interviews and many more
while collecting crucial data about
customer wants and desires.
The big data is collected with the help
of modern tools such as machine
learning as well as Artificial
Intelligence.

Explaining about the ways in which the
information is stored
Database: The term database is defined as the structured collection of critical information or data which is stored in
the computer system in electrical format. The following are the three types of database which will show how data is
collected in different ways:
Relational database:
In this type of database, the information is collected and organised in the logically independent table
formats which consists of multiple rows and columns that relate to each other. This database provides support for the
organisation in terms of deleting or updating data effectively(Giacalone, Cusatelli and Santarcangelo, 2018).
Network database:
In this the data is stored in the form of hierarchical structure. The data in network database is stored in
stored in such a way that ensures all entities are properly structured in graphical representations.

Description of the impact of technological
development on the use of data for decision
making process
The growth in technology completely altered the way data is collected as well as used in order to formulate an
effective strategies decision. In context to Sainsbury's company, the update of traditional market research techniques
into machine learning analytical tools supported the company in the positive manner as the change leads the
organisation to make cost effective as well as more accurate predictions related to current market trends and
customer needs and wants. The innovation of technology gave birth to big data technology that favourably assists the
firm to understand complex grocery trends and also supports the organisation to know timely about what products
are getting famous among their customers

Analysing about the strategic importance of
data in day to day operations of organisation
In context to Sainsbury's organisation, The big data technology supports the firm to make evidence based decisions
by collecting as well as analysing information from different digital platforms such as social media platforms. The
data collected through machine learning and AI technologies helps the firm to ensure smooth operations of its
business activities as well. The Big data greatly assists the firm to optimise its business performance by gathering
accurate market trends in the most cost effective and timely manner. Moreover, Sainsbury's firm practice the usage of
data drawn from big data technologies towards managing various areas of its business. The first is that the
information collected is used by organisation to grow its better produce. In relation to this, the firm uses big data
information in order to discover better dairy products through identifying best livestock feeding practices.

Evaluation of ways to improve data capture
as well as usage in the firm
The data is most crucial part for the organisation in order to make accurate and data based decision making for
achieving customer satisfaction level. In context to Sainsbury's, the following effective data capture strategies can
support the firm to gather information in the most efficient manner:
Setting guidelines:
In this strategy, the company can formulate a certain guidelines such as using proper abbreviations,
using capital letters for the top companies with proper spellings. The firm by setting correct guidelines can prevent
duplication of data.
Ensuring compliance and continuity:
The compliance of set guidelines by the staff members of company and continuity can help the
organisation in decreasing the collection of outdated customer information.

Conclusion
It has been analysed from above report that Big data technology is becoming essential for the firm in order to gain
deeper insights about current market trends as well as customer wants. The report was able to explain that
implementing big data technology in decision making process support the firm to make timely and accurate
decisions. In addition to this, it has been concluded that big data techniques is better than traditional market research
techniques. The report has also covered about types of databases and management information system.

References
 Al Hadwer, A., Gillis, D. and Rezania, D., 2019, March. Big data analytics for higher education in the cloud era.
In 2019 IEEE 4th international conference on big data analytics (ICBDA) (pp. 203-207). IEEE.
 Fernando, Y., Chidambaram, R.R. and Wahyuni-TD, I.S., 2018. The impact of Big Data analytics and data
security practices on service supply chain performance. Benchmarking: An International Journal.
 Giacalone, M., Cusatelli, C. and Santarcangelo, V., 2018. Big data compliance for innovative clinical models. Big
data research, 12, pp.35-40.
 Mishra and et.al., 2018. Organizational capabilities that enable big data and predictive analytics diffusion and
organizational performance: A resource-based perspective. Management Decision.
 Rajabion, L., 2018, December. Application and adoption of big data technologies in SMEs. In 2018 International
Conference on Computational Science and Computational Intelligence (CSCI) (pp. 1133-1135). IEEE.

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