A Report on Data Insights for Business Decisions and Market Research

This report explores the crucial role of data insights in modern business decision-making, highlighting the differences between orthodox market research and big data. It details how information is captured and stored using various databases and management information systems, and how organizations leverage this data for daily operations. The report also outlines a research approach for improving data capture and utilization within the retail sector, emphasizing the impact of technological advancements on data use. Ultimately, it concludes that a deep understanding of data is essential for developing effective strategies and driving business growth. Desklib provides access to similar solved assignments and resources for students.

Data insights For
Business Decisions

Table of content
 Introduction
 Types of data is collected and used by the organisation
 Describe orthodox market research and how this is different from Big Data
 Explain how information is captured and stored with key references to types of
databases and management information systems
 How information and data is used in organisation
 Outline for research into improving data capture and use in a sector
 Conclusion
 References

Introduction
 Data insight is defined as the deep understanding of
an individual or organisation regarding a particular
issue. This depth understanding enables business to
take better decisions as well as lead towards right
direction. Big data is the collection of data that is
huge in volume and growing exponentially with time
(Ennouri, and Mezghani, 2021).

Types of data is collected and used by the
organisation
Data is considered as the collection of information that is
organised and synthesized through analytics and in business for
taking better and effective decisions.
 Big data: Big data is defined as the large as well as diverse
set of information that is complex and grow at ever-
increasing rate.

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 Primary data: Primary data is defined as the first hand data that is collected by
the researcher himself as per their needs and demands.
 Secondary data: Secondary data is defined as the data or information that is
collected by the someone other than the primary users. It is collected for some
other purpose and already exist so it is more cheap and quickly obtainable than
primary data.

Describe orthodox market research and how this
is different from Big Data
Orthodox market research: Orthodox market research is
defined as the wide concept that incorporates advertisement
as well as marketing. There are various tools and techniques
are included in this market research to gather required data
or information. It concentrates on taking assessment of
overall market for specific products and services.

Difference between orthodox market
research and big data
Orthodox market research Big data
Orthodox market research represents data
in structured form that makes it easy to
understand and recognise.
In big data, information and data is
represented in unstructured or semi-structured
form because data is stored in large number.
In this research size of data is very small
and it is represented in centralised manner.
Big data is deals with large and complicated
data. It is difficult to handle.
It requires normal system configuration for
processing data.
High system configuration is required to
process the data.
Traditional database tool and techniques
are used to store and use data.
Special tools and techniques are used manage
and handle big data.

How information is captured and stored with key references to
types of databases and management information systems
Database: Database is defined as the information which is set up for easy access,
manage as well as updating. Database store aggregation of data records and files that
contains relative information like financial and product information, customer data,
sales transactions and various other. Data or information is captured and stored in the
different types of database in standardized manner. Some types of database that
stored information are mentioned below:
 Hierarchical database system
 Networking database system
 Objective-oriented database

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 Management information system: It is defined as
the information system that is used by the
organisation to control, analyse, coordinate and
visualise information in efficient manner. It
facilitates the retailing sector to gather their data
from different online system, analyse the
information then in the last report data to aid in
management decision-making (Montakhabi, 2022).

Impact of technological development on the role and use of
data in the business decision making process within your
chosen sector
 Technological development is defined as the process that is related to
the invention, innovation as well as diffusion of technology or
processes. In current business environment, various advancements and
developments are take place that directly and indirectly impact the role
and use of data in the business decision-making process in retailing
sector.
 Predictive analytics
 Data visualisation
 Data processing

How information and data is used within the day
to operations of organisations
 Data or information is the essential plain facts that is related to the internal as well
external environment and used by the organisation to perform daily operations of
business in efficient manner. Business uses their customer data which is the
matrices related to the customer interaction.
 Inform and improve business decision-making: Tesco uses data to make better
and effective business decisions related to daily activities such as how to
operations, allocation of resources at each department, warehousing to
distribution, marketing to customer service and various other.

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 Revamp and refine operations: Tesco uses data for
the purpose of optimising operations as well as
everyday business process. Any virtual business
process which generates data related to the customer
ordering system or machines on a production is
conducted or refined in the bases of insight the data
provides. It enhances organisational operations
efficiency.