Big Data Analysis and Its Impact on Business: Characteristics, Challenges, Techniques, and Technologies

This report discusses big data analysis and its impact on business. It covers the characteristics of big data, challenges faced in big data analytics, techniques used for big data analysis, and technologies that provide support to businesses. The report also highlights the importance of big data technology in providing better insights, privacy and management, and data-driven innovation.

Information Systems and
Big Data Analysis

Contents
Contents...........................................................................................................................................2
INTRODUCTION...........................................................................................................................1
MAIN BODY..................................................................................................................................1
Big data........................................................................................................................................1
Characteristics of big data...........................................................................................................1
Challenge for the big data analytics:...........................................................................................2
Techniques for big data analysis..................................................................................................3
How big data technology provide support to business................................................................3
CONCLUSION................................................................................................................................4
REFERENCES................................................................................................................................6

INTRODUCTION
Big data analytics is considered a complex process for purpose of examining of big data which
identifies different information related to preferences of the customer, correlations, hidden
patterns, market trends and other things (Huang, Wang and Huang, 2020). This project report
includes big data as well as its characteristics of the big data. It also includes different types of
challenges that occur in Big data and also the technology used by businesses. Moreover, it also
includes big data technology that provides support to businesses.
MAIN BODY
Big data
Big data can be described as field in context to the analysation and extracting of information
from different sets. It is also a term that is linked with the large among of data that is growing
day by day. These data are humongous as well as complex and due to this, there is no
conventional data management tool can be able to process as well as store it. For instance, there
are different types of social media platforms used by businesses that gather data of consumers for
purpose of improving their services. It is one of the trending terms in today’s time with the
development of industry and changing trends in the industry (Kozmina, Niedrite and Zemnickis,
2018). The focus of businesses is on collecting a variety of data which is important for business
in order to improve the service. Big data is used by the business for purpose of understanding the
patterns, association and trends in the market but understanding of data is a complex process and
also it is challenging.
Characteristics of big data
It is important for a business to understand the characteristics of big data in order to understand
how to use it and also how it works for them. There are different characteristics of big data
which are mentioned below:
 Velocity: It is one of the important terms which explains the speed of data processing. It
is essential for the business to have high velocity in their organisation which is important
in order to process big data. It is one of the components which includes the rate of change
linking income sets, activity burst and other things (Wang and Wang, 2020). It is
important for businesses to develop the capability for purpose of processing of data in
less time as it allow them to take advantage of opportunity.
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 Volume: Volume is the amount of data possessed by a company that helps them to
improve the efficiency of its business. The volume of data is measured in form of
gigabytes, yottabytes, zettabytes and other things. There is an increase in the volume of
data day by data with changing trends in the industry. It creates problem for business to
carry such a large amount of data and also to organise it (Li and et. al., 2022).
 Variety: Variety is another characteristic of big data as it comes in different forms.
Variety creates issues for the company as it creates an impact on the performance. It is
difficult for the business to manage the data in an effective manner. Variety is linked with
the source from where data is gathered. These data can be collected by businesses in
different forms like structured, semi structured and unstructured.
Challenge for the big data analytics:
Big data analytics is one of the complex process which is used by business for purpose of
examining of big data that cover different patterns, correlations, customer preferences and
market trends in the marketplace and also helps them for purpose of making an effective
business decision. It is a process that provides different benefits to business but at the same time,
it is also creating various challenges. Explanations of some of these challenges for purpose of big
data analytics are mentioned below:
 Fails to provide timely insights: Business gather data in large volumes from different
sources in order to improve their service. These data are in different forms and business
needs to make effort for purpose of making it in structured forms. These data are more
complex and it becomes difficult for businesses to understand these data (Martins and et.
al., 2020). It does not allow businesses to understand timely insights of consumer data.
 Issues in the security of data: It is another challenge that occur in the big data analytics
which make it difficult for the business to understand, store as well as analyse different
types of data sets. Companies also consider data security as the later stage which is not
the right move for them. Due to security threats, company can lose its image as well as
marketing share in the marketplace.
 Lack of professionals available: In order to implement and use big data analytics in the
business, professionals are required who have proper knowledge of big data technology
and ways to use it in an effective manner (Yang, 2021). It is important for the business to
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hire professionals in business but there is a lack of availability of skilled people in this
industry which is a major challenge.
Techniques for big data analysis
There are different types of tools and techniques for purpose of big data analysis which helps
businesses for purpose of improving their service. An explanation of some of these techniques
for big data analysis is mentioned below:
 A/B testing: It is a randomisation of the experimentation process where there are two or
more versions are available to different segments of website visitors in order to identify
which version is more impactful for the business. It is a technique used by businesses in
order to analyse the data of consumers for the business (Novak, Bennett and Kliestik,
2021). It is a method used by businesses for purpose of ensuring changes in the marketing
strategy and the product which is important in a data-driven world.
 Data mining: it is a process that aims to sort out large sets of data in order to identify
different patterns of relationships for purpose of solving problems in the business. It is
important for the business in order to predict different trends of business in the future and
also enable them to make the informed decisions. It is essential for businesses in order to
find out the suitable segment for the business.
 Machine learning: Machine learning is one of the techniques which consists use of
different software in the business which is learning from the data. It provides the ability
to the computers in order to allow them to learn and also predict things on basis of this
learning (Palacio and López, 2018). It is important for businesses in order to improve
their service and make it according to the needs and requirements of customers.
How big data technology provide support to business
Technology plays important role in order to get the success of the business. Business in today’s
time is highly dependent on technologies which is important for providing support to the
business. There are different types of technologies that provide support them are mentioned
below:
 Better insight of business: It is essential for businesses to use customer insights in their
operation for improving the business and also the increasing effectiveness. Big data
technologies is also playing important role for the business in order to get data of
customers in effective manner and utilising it in their offering (Zhou, 2020).
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 Privacy and management: Big data technology is also important for businesses as it
helps businesses to protect their data from others. It helps them for the purpose of
managing the data in an effective manner that allow them to make quick decisions (Vasa
and Thakkar, 2022).
 Data-driven innovation: Innovation is essential for business in order to increase
competitiveness in the marketplace and also for the purpose of introducing something
new in the market. Big data technology allow the business to understand the needs of
customers and introduce innovation according to those needs.
CONCLUSION
From above mentioned project report, it can be concluded that data management is essential for
business. It is used by businesses for different reasons which is essential for them in order to get
success. It has different characteristics which make it more useful for the business. It is creating
different benefits for their business as it allows them to adopt innovation according to the
requirements of customers, manage privacy in business and other things. It also consists of the
use of different types of technology like machine learning, data mining and A/B testing. It is also
a technology which is creating challenges for businesses fails to provide timely insights, creating
issues in the security of data, lack of professionals available.
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REFERENCES
Books and Journals
Huang, C.K., Wang, T. and Huang, T.Y., 2020. Initial evidence on the impact of big data
implementation on firm performance. Information Systems Frontiers, 22(2), pp.475-
487.
Kozmina, N., Niedrite, L. and Zemnickis, J., 2018, July. Information requirements for big data
projects: A review of state-of-the-art approaches. In International Baltic Conference on
Databases and Information Systems (pp. 73-89). Springer, Cham.
Li, X., and et. al., 2022. Big data analysis of the internet of things in the digital twins of smart
city based on deep learning. Future Generation Computer Systems, 128, pp.167-177.
Martins, A., and et. al., 2020, April. An evaluation of how big-data and data warehouses improve
business intelligence decision making. In World Conference on Information Systems
and Technologies (pp. 609-619). Springer, Cham.
Novak, A., Bennett, D. and Kliestik, T., 2021. Product Decision-Making Information Systems,
Real-Time Sensor Networks, and Artificial Intelligencedriven Big Data Analytics in
Sustainable Industry 4.0. Economics, Management & Financial Markets, 16(2).
Palacio, A.L. and López, Ó.P., 2018, May. From big data to smart data: A genomic information
systems perspective. In 2018 12th International Conference on Research Challenges in
Information Science (RCIS) (pp. 1-11). IEEE.
Vasa, J. and Thakkar, A., 2022. Deep Learning: Differential Privacy Preservation in the Era of
Big Data. Journal of Computer Information Systems, pp.1-24.
Wang, S. and Wang, H., 2020. Big data for small and medium-sized enterprises (SME): A
knowledge management model. Journal of Knowledge Management, 24(4), pp.881-897.
Yang, X., 2021. Business big data analysis based on microprocessor system and mathematical
modeling. Microprocessors and Microsystems, 82, p.103846.
Zhou, M., 2020. Financial auditing big data platform based on FPGA and convolutional neural
network. Microprocessors and Microsystems, p.103461.
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