Data Insight for Business Decisions: Analysis of ASOS plc Data

This report provides a comprehensive analysis of data insights for business decisions, focusing on the application of data in the context of ASOS plc. It begins with an introduction to data and its importance, followed by a detailed exploration of various data types, including big data, structured, unstructured, semi-structured, primary, and secondary data. The report differentiates between orthodox research and big data, highlighting their key differences in terms of data collection, analysis, and scalability. It then examines different types of databases and management information systems, such as centralized and distributed databases, and their role in data storage and management. The report further discusses the impact of technology on data collection and usage, emphasizing how companies like ASOS plc leverage data to understand customer behavior, improve customer experience, and optimize marketing campaigns. It concludes with recommendations on how businesses can enhance their data usage for better decision-making, along with references to relevant research and literature. The report offers insights into the practical application of data analysis in a business setting.

DATA INSIGHT FOR
BUSINESS DECISIONS

TABLE OF CONTENT
• Introduction
• Types of data
• Big data
• Primary data
• Secondary data
• Orthodox research and difference between big data
• Type of database and management information
system
• Impact of technology on data
• Uses of information and data
• Outline to improve the data uses
• Conclusion
• REFERENCES

INTRODUCTION
• Data refers to the collection of information, facts, observations.
• Data is being collected by every company and organisation to know more about
customer and market.
• In this report data collection for ASOS plc has been mentioned.
• ASOS plc is a British online fashion and cosmetic retailer, who's headquarter is
situated in London.
• This company deals in fashion, cosmetics, clothing and accessories.
• In this report various types of data is elaborated such as – Big data, primary and
secondary.

TYPES OF DATA
Big data
• Big data refers to the collection of those data which is huge and the volume of such data is high.
• Big data can be collected in structured, Unstructured and semi- structured form.
• Structured
• Data which can be stored, gathered and processed in the fixed format is known as structured data.
• Unstructured
• Data which does not have any structured form is referred as unstructured data.
• Semi- structured
• This data contains both the data collection method it can be collected through structured and unstructured.

CONT..
Primary data
• Primary data is being collected by researcher directly. This data mostly collected for research project.
• These data are often authentic and reliable.
• Secondary data
• These data is already being collected in the past and available for others.
• Secondary data is easily available and accessible.
• Data used by ASOS
• Asos uses big data to know about their potential customers as the company is targeting young adults,
with the help of big data company get to know about the age, gender, residence etc.

ORTHODOX RESEARCH AND DIFFERENCE
BETWEEN BIG DATA
• Orthodox research show the collection of data in the old and traditional manner which is
being used by all the companies to collect the necessary information of their customers.
Orthodox research Big data
Orthodox data is relied on fixed scheme
and it is static in nature and it works with
structured data only.
Big data is dynamic in nature, besides this,
it includes structured and unstructured
data.
This data take place after the event is being
analysed.
This data is being analysed in real time.

CONT..
Orthodox research Big data
It is totally based on centralized database It uses distributed architecture, which makes it more
scalable as compared to orthodox research.
Data collected from orthodox research is limited,
because it is collected on hourly and daily basis.
It is unlimited, because it is gathered on per second.
Normal system can process traditional data. High and advanced system requires to process big data.
Data collected from orthodox can be manipulated by
normal function.
Special functions need to manipulate such data.
Orthodox data can get managed. It is hard to manage

TYPE OF DATABASE AND MANAGEMENT
INFORMATION SYSTEM
There are various types of database and management information through which data can be stored.
• Centralized database
• The information is collected and gathered from centralized and different locations. It also
includes various authentication, verification and validation of the user.
• Distributed database
• This is the opposite of centralized database, it uses common database to capture the
information.
Data collected by ASOS plc
• Asos plc don't collect information from the customer without their permission, they gather information
only when the customer knowingly provide them.

IMPACT OF TECHNOLOGY ON DATA
• The broad adoption of internet and smart phone have become easy for companies
to gather customer data. But earlier collecting data on large scale was not so easy.
• Earlier companies collect the data of customer by going door- to- door but now
with the help of technology it becomes easy for the company to touch the
customers at any time.
• Now the auto generated feedback help the company to know what, customer
thinks about their products what should they improve etc.
• ASOS plc use different software to store the data and just is a click, company can
see the information of their thousands of customers.

USES OF INFORMATION AND DATA
• ASOS plc uses the data, to improvise the customer experience, if they receive any negative feedback from
any customer the company can work on it and serve the customer as per their demands and expectations
• Apart from this, data helps the company to make certain changes in their marketing and promotional
campaigns and this will help the company to increase sells and profitability.
• As ASOS is a fashion retailer so the data will help the company in its day to day operations. Owing to data,
company can know what is the trend going on in the fashion industry, what type of product liked by the
customers.
• As per the data company can manage its everyday operations like – how many demands for their products is
there in the market, how much product they should introduce in the market so that company can earn profit.

OUTLINE TO IMPROVE THE DATA USES
• Asos plc can improve the uses of captured data, with the help of data company can come
to know that what type of customer is addicted to their product- are they youngster, adults
or old age people.
• Company can also get to know about the region and localities, like in which region their
product is more demanded and in which region ASOS plc is lagging behind from its
customers.
• So with the help of such data company can increase its sales and revenue by improving
the usage of collected data.

CONCLUSION
• After analysing the entire report, it can be concluded that, this report speaks about the
uses of data for making business decisions.
• This report states about the types of data and also the difference between the orthodox
and big data.
• How a business collects data is also mentioned in this report and how a company stores
and safeguard the valuable data of customers.
• Impact of technology on the collection of data is also explained in this report.
• Various recommendation has been given to the company is defined in this report.

REFERENCES
• Delpechitre and et.al, 2019. The dark side of technology: examining the impact of technology overload on
salespeople. Journal of Business & Industrial Marketing.
• Ferguson, A.G., 2017. The rise of big data policing. New York University Press.
• Gnann and et.al, 2018. Improving copula-based spatial interpolation with secondary data. Spatial
statistics.28. pp.105-127.
• Haddad and et.al, 2020. The impact of technology readiness on the big data adoption among UAE
organisations. In Data Management, Analytics and Innovation (pp. 249-264). Springer, Singapore.
• Johnston, M.P., 2017. Secondary data analysis: A method of which the time has come. Qualitative and
quantitative methods in libraries.3(3).pp.619-626.