Big Data Analytics in Business Management: Challenges and Techniques

This paper discusses the concept of big data, its characteristics, challenges, and techniques for analysis. It also explains how big data technology can support businesses with examples.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data Analysis
Poster and Accompanying Paper
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Contents

Introduction p
What big data is and the characteristics of big data p
The challenges of big data analytics p
The techniques that are currently available to analyse big data
p
How Big Data technology could support business, an explanation with examples
p
Poster p
References p

INTRODUCTION
The term business management can be defined as the proper administration of the
business organisation. In order to do the business administration, big data is required. This is
because the big data provides the adequate information related to the business operations to the
management of the company. The big data is the set of information stored at one place. These
information is being used by the business organisations for making the long term and short term
plans for the company(Keyes and Westreich, 2019. It also evaluate and analyses the business hurdles
as per the current business scenario in the country. This presentation would discuss about the
concept of the big data. It would also discuss about the hurdles and challenges that is being faced
by the big data in the present market scenario.
MAIN BODY
Big data and its characteristics-
The big data is the complexed structured set of data that is being utilised by the business
organisations. These also discuss about the different sources of getting the information on
internet. The big data connects the different information at one place. In the present scenario, the
data is made at any time. Moreover, it also results into immense accumulation of important
information through which the arrangement and entity is required for administration, storing,
visualization and evaluating. The customary tools of data which is not created for negotiating the
huge volume along with the complicated, that would eventually decrease the particular software
of big data. This would too help in resolution of building plan for load administration. The
platforms is too related to big data are especially designed for carrying on the huge amount of
data that would come to the systems at high speed and huge assortment.
Features
 Volume- The big data is itself showing the size of data that is always in huge volume.
The data value is ascertain the size of the information. Generally, it all depends on
volume of the information that whether it would be consider as big data or not in the
organisation. It is too considered as a characteristic which is necessary for being
acknowledged while dealing with resolutions for the big data.
 Variety- It could also be referred as the heterogeneous source along with the nature of
data that is being structured and unstructured both. In earlier days, the computer

programs and the databases are top of the data which is being executed by most of the
application. On the other hand, it can be seen that in today's time data is considered in
form of photos, videos, email, monitoring devices, audio etc., So, the application analysis
of the data is required. This is unambiguous data that is being increased by the challenges
for storage, mining and analysing data)(Cox, 2018).
 Velocity- This is the data which is generating the speed. It also analysis how fast the
speed is made and prepared for getting the requirements by determining the actual
potentiality of the specific data. These velocity of big data too deals with the pace by
which the data is moving from the various beginning sources such as application logs,
social media sites, businesses process, cell phones and different networks. Moreover, the
flow of data is huge and constant.
 Variability- It is too referred as the inconsistency that has been showed by data at
different times. Hindering the process of being able for handling and carrying off the
data in an effectual manner.
 Veracity- It shows about the accuracy and quality of data. This data is collected by few
missing elements that can be general or not capable to supply real and essential insights. It is
totally based on the trust level while collecting the information for the big data. Moreover, the
collected data could be difficult and complex in case of taking it in use. Moreover, it would
create confusion rather than giving insights.
Big Data challenges
The below given are the some challenges of big data analytics-
 Mess of visualization of data- The reporting a level of interference is very high. So, it is
hard to find the essential information for the organisation. Moreover, these complexity
would be resolved by UI or UX specialist that would provide assistance in developing the
interface that is flexible and very easy of manoeuvrer to work with in the business
organisation(Konanahalli, et.al, 2018).
 Inefficient arrangement of data- The organising of data is the very difficult part to
work with in the company. This is a great to check whether the warehouse of data is
being planned in accordance with usage of case scenarios.

 Data sharing- Through the admittance of data from the governmental depository that
results in having different issues as well as it can take to considerable issues as the data is
immense in terms of size.
 Outdated technologies- The modern technology that is necessary of processing more
bulk of data in very fast way along with an cost effective way. So in nearer future the
technologies that is being utilised with regard of big data analytics would be
superannuated. Hence, it would require more resources.
 Non optimal structure- In case of the cost variable, it is always a possibility for doing
alteration. In the cloud resolution, you pay for the usage of decreasing the cost.
 Poor choice of data source- In condition where the system is based on the data that are
having the faults or errors which is not fulfilled, then these kinds of data would get
generated for the poor results. The procedure of validation of data along with the
managing of data quality is being covered at the stage of ET procedure that would assist
in rising up the quality of data in the organisation)(Willetts, Atkins and Stanier, 2022.
Techniques presently available for analysing the big data
These are some of techniques that is required for the analysis of big data in the
organisation are discussed as follows:
 A/B TESTING- These are the various types of groups are use to compared by the
primary dominant groups that is having the purpose to determine the management that
would increase the goal component. This is basically it happens where the two than two
components are compared with each other to gained the tool for analyse and achieving
the aims and goals.
 CLASSIFICATION- There are different number of method that is being used for
deciding the categories that the newer data belongs along with the monitor the learning
that would aid in making of decision by endeavour of various class.
 ANALYSIS OF SOCIAL NETWORK- This is used to enhance the relationship
between the concern and consumers for good understanding the social model of the
customer and the first one was telecommunication business who are using it along with it.
This can be used by various scientists for searching the social conception. This would
also evaluate the bond among the individuals in the organisation. Along with this, the
activities of businessman with their modes of finding of individuals that are already in the

schemes while deciding the relations between the singles for analysing the use of the
social network as well as examining the connections among the customers and
individuals of the concern.
How the Big Data technology could aid in business, explanation with instances.
 COMMUNICATION WITH CUSTOMERS- These are the consumers base are
brilliant enough for knowing their priorities as per the recent time to explore everything
before purchasing it. Communications could happen to the concern by several platforms
on the social media. These businesses is too capable to reach the customers by the help of
the big data while interacting with the tailored by knowing its desires as well as the
products as per its needs .
 RISK ANALYSIS- This means the analysis of the organisation that would effect the
operations of the concern. It aid in the replication of feed of the public media, newspapers
reports for knowing the current need of market because it would give the aid to the firms
in discernment the current marketplace competition. It would also do modification in the
product as per the competition in the market place)(Pantano, Giglio and Dennis, 2020).
Conclusion
This presentation summarises about the concept and meaning of the big data. It also
concludes about the techniques that is being used in examining the big data by the different
organisations. This also explains about the challenges that are being faced in evaluating the big
data in a business concern.

POSTER

REFERENCES
Books and Journals
Keyes, K.M. and Westreich, D., 2019. UK Biobank, big data, and the consequences of non-
representativeness. Lancet (London, England), 393(10178), p.1297.
Cox, N., 2018. UK Biobank shares the promise of big data.
Konanahalli, A., et.al, 2018. Big data: a new revolution in the UK facilities management sector.
Willetts, M., Atkins, A.S. and Stanier, C., 2022. Quantitative Study on Barriers of Adopting Big Data Analytics for
UK and Eire SMEs. In Data Management, Analytics and Innovation (pp. 349-373). Springer, Singapore.
Pantano, E., Giglio, S. and Dennis, C., 2020. Integrating big data analytics into retail services marketing
management: The case of a large shopping center in London, UK. In Handbook of Research on
Innovations in Technology and Marketing for the Connected Consumer (pp. 205-222). IGI Global.