MG413 Presentation: Information & Data in Business Decisions

This presentation provides an overview of data management and its role in business decision-making, particularly within the retail sector. It covers the types of data collected (primary and secondary, including Big Data), the differences between orthodox market research and Big Data, and the methods of capturing and storing information using databases and management information systems. The presentation also discusses the impact of technological development on data use, the strategic importance of data in day-to-day operations, and an outline for research to improve data capture and utilization within an organization. References to academic sources are included to support the analysis and findings.

DATA MANAGEMENT

TABLE OF CONTENT
1. Type of data collected and used by the organisation and if this is Big Data, and if this is primary or
secondary data
2. Orthodox market research and how this is different from Big Data
3. The way information is captured and stored with key references to types of databases and
management information systems
4. The impact of technological development on the role and use of data in the business decision
making process within your chosen sector
5. The way information and data is used within the day to operations of organisations within that
sector and what is its strategic importance to the organisation within its sector
6. Outline for research into improving data capture and use in a sector/organisation

Type of data collected and used by the organisation and if this
is Big Data, and if this is primary or secondary data
• The organisations generally prefer to collect
secondary data in order to collect precise and
systematic data (Ferraris, Mazzoleni, and Couturier,
2018).
• The secondary data helps an organisation to make
quick decisions and cost effective approach.

Orthodox market research and how this is different from
big data
• The orthodox market research is considered as
key approach in research as it includes ideas and
beliefs which are preferred by most of the people.
• Big data includes information and data is
represented in unstructured and semi structured
form. The Big data includes large amount of data
and orthodox market research includes less data.

The way information is captured and stored with key
references to types of databases and management
information systems
• The information is stored and captured
in different types of databases and
management information systems in the
form of tables (Lai, Sun, and Ren,
2018).
• Tables are most simplest form of storing
an information for a longer time period.

The impact of technological development on the role and use of data in
the business decision making process within your chosen sector
• The information and technology plays a
key role in facilitating decision making
with the help of decision support system.
• Technological development also increase
the chances of data security and other
major cyber security issues (Piryonesi,
and El-Diraby, 2020).

The way information and data is used within the day to
operations of organisations within that sector and what is its
strategic importance to the organisation within its sector
• In the retail sector, the information is stored with
the help and support of advanced computer
systems and software.
• The information is used to perform data analysis
and also calculate management of data with
appropriate approach.
• The information is also used in day to day tasks
of the company to manage key operations
related to big data management.

Outline for research into improving data capture and
use in a sector/organisation
• In order to improve data capture, a retail
sector organisation must take support of
information and technology (Qi, 2020).
• The organisation can also choose big data
management and improve business
functioning. The organisation can also focus
on primary and secondary research in order to
increase chances of precise data collection.

REFERENCES
Ferraris, A., Mazzoleni, A., and Couturier, J., 2018. Big data analytics capabilities and knowledge management:
impact on firm performance. Management Decision.
Lai, Y., Sun, H. and Ren, J., 2018. Understanding the determinants of big data analytics (BDA) adoption in
logistics and supply chain management: An empirical investigation. The International Journal of Logistics
Management.
Piryonesi, S.M. and El-Diraby, T.E., 2020. Role of data analytics in infrastructure asset management: Overcoming
data size and quality problems. Journal of Transportation Engineering, Part B: Pavements, 146(2), p.04020022.
Qi, C.C., 2020. Big data management in the mining industry. International Journal of Minerals, Metallurgy and
Materials, 27(2), pp.131-139.

THANK YOU