Information Systems and Big Data Analysis: Characteristics, Challenges, and Techniques

This report analyzes the concept of big data in relation to its methods, techniques, and characteristics. It also highlights the challenges faced by the IT industry and how big data helps businesses.

Big data

Table of Contents
Introduction...........................................................................................................................................3
What is big data and its characteristics?............................................................................................3
Challenges of big data and the techniques which are available to analyses big data........................4
How big data technology support business.......................................................................................5
Conclusion.............................................................................................................................................5

Introduction
This report aims to analyses the concept of big data relation to its methods, techniques and
characteristics. In IT industry big data has taken a rapid growth due to emergence of digital
technology in every business field. Big data refers to those information, record and actions of
customer that kept in software for future purpose (Hung, He, and Shen, 2020). Due to having large
usage of computers mobile and other electronic devices, the emergence of big data is become
necessary. Therefore, this report is going to present the use of the data and how it applies in many
organisation. Also there will be evaluation of techniques and challenges which are faced by IT
industry. In addition to this, how big data help businesses is also going to highlight in this report.
What is big data and its characteristics?
Big data is the concept of large data integrated by business software in terms of documents, files ,
images and any other formats. The IT industry is heavily dependent upon big data consideration as it
becomes a day to day need of IT companies to make profits in provide Customer services. Internet is
being an essential part for every individual. People are rapidly using social media platforms through
internet configuration that include a large data management for IT companies. Therefore, some of
main examples of big data software hand hoop, spark, hive and cloud. It undertakes a function of data
management, cloud protection, data analysis and interpretation. The companies are required to make a
safer and best use of this data. There must be privacy protocols and measures to prevent from any
fraudulent activities. It refers to all the user details and important documents that should not be shared
through third party. These are the large and complex data base which is certain through different
sources. There is requirement of huge and integrated software’s to contain big data. Many companies
change their ways from traditional to modern in order to keep the data safe in secure. Traditional
processes are not so longer taking success in modern market for that instance, company’s upgraded
and innovative software’s for the same.
Characteristics of big data
As the name says that, the data collects in a big and use formats so it requires various types of
sources and volume. Therefore the main characteristics of big data are described below:
Volume of data: the big data consume a large volume which requires Expendables software’s. This
data are of large in size, format and structure that require use space to store in a secure manner
(Herschel, and Miori, 2017). Therefore, an IT company has to establish good working team who
could take care of the volume of big data. As the Twitter itself generates 7 TB of data everyday.
Variety of data: the data are gathered and collected in a lot of varieties. The business
undertakes data in various formats, files structures, webpages and many more. Therefore the

companies need to analyze videos varieties in order to make it safely installed. Mainly these data are
semi structured, unstructured and structured. So the companies need to maintain all types of data to
provide better Customer services.
Velocity of data : it refers to the speed at which the data get flow and reach to customers or
organisation software. It shows how quickly the data is receiving to the user and the companies made
it possible in a systematic manner (Knoppers, and Thorogood, 2017). Therefore, the velocity must
be maintained at a normal range that could satisfy the search of audience. These velocity must not be
outsourced or fact and maintain it in a privacy.
Challenges of big data and the techniques which are available to analyses big data
As far as internet is taking Rapid rise in global business environment. Big data is also become
a challenge for companies to maintain and store it in a proper way. The company's focus on relying
upon these big data in order to provide customer satisfaction. Therefore the challenges come across
while managing and developing and storing big data. It requires need for data analysis to ascertain the
challenges in repair strategies for future growth. The challenges are mentioned below:
Data integration: it is a major challenge in the field of big data Technology. It refers to
gathering data from number of sources that may dispersed or create flaws in between the search. The
IT expert team needs to put more focus on researching and analyzing the data sources.
Data complexity: nowadays, data are become crucial part for business as well as it comes with many
complex situations. Therefore, the IT managers need to analyse these complexities and try to handle it
in a proper manner (Mariani, 2019). The more complexities will be come, the more companies will
be able to provide better services to audience. These data take many changes and rigidity due to
having many sources and formats.
Data security: it is one of the remarkable challenges in the history of big data. Not only
organization but also the users facing challenges through lack of privacy control and protective
measures for big data. It leads to result in theft of customer’s details through Malware and hacking
practices (Poel, Meyer, and Schroeder, 2018). Therefore the managers need to look severely upon
data security issues or else the organizations would face major drawbacks in society.
Techniques for analyzing big data:
Data mining: it is one of the effective tool for analyzing big data in a simpler manner. It
helps in mining data from large complexities true machine learning.
Machine learning: it is also the most used software or tool by many business organisation. It
refers to the concept of artificial intelligence in which the data are programmed in the way it has been

performed. It is based on computer science and algorithms which provide data through broader
perspective.
Statistics : the data is gathered through collecting information and variables from any user
interferences. This technique of data analysis is an expensive form that develops by time. Business
statistics could be helpful for giving insight about product and services, figures and facts and many
more.
How big data technology support business
The world is supporting digital era and going forward towards internet and data uses.
Therefore, big data enables as a support system for many IT companies. It contributes in you success
and growth for business which are based on information technology. Companies like Facebook and
Twitter are all a part of big data which has taking a leading growth in market. It gives a competitive
position in digital world. This big data support this is true following ways:
Management of data: the technology helps in managing data in a large Manner. The
companies which deals at global level and have digital presence are mostly successful with the
contribution of big data Technology (Benhlima, 2018). It helps in keeping data stored for long time
without making any changes. Facebook is top most company who consist large data through this
technology and enable a reputed brand name in global market.
Privacy of data: in the digital context, it is become easy to save files, documents and any
information in the form of big data. It eliminates traditional way of keeping use materials for long
time and change away to secure these data within privacy control. With data Technology gives a high
power for keeping security a major concern for both organisation and customers. Due to which,
organizations like Twitter and Amazon are taking a rapid growth by being a safer place for customer
interference.
Customer engagement : big data provides Technology provide an opportunity in terms of
undertaking large customer engagement (Gillan, and Whelan, 2017). The organizations can take
arrival of use audience at websites and other digital platforms through using big data software and
tools. Customer engagement is the main aim of every organisation that must be fulfill by IT
Department. Organizations like Facebook , Amazon use customer engagement tools through which
they analyses what the people want and enable their engagement towards organization.
Conclusion
The report has concluded that big data technology is being scattered in all over the
globe. It shows how the data is gathered, stored and used in various ways. The big data has

characterized in in volume velocity and variety which describes its size speed and type.
Therefore, the report has identified various challenges through big data Technology that must
be overcome by effective expert’s knowledge. As it is analysed that big data Technology
contribute in growth and success of many big companies through customer engagement
management of data and privacy control.

References
Books and journals
Hung, J.L., He, W. and Shen, J., 2020. Big data analytics for supply chain relationship in
banking. Industrial Marketing Management, 86, pp.144-153.
Herschel, R. and Miori, V.M., 2017. Ethics & big data. Technology in Society, 49, pp.31-36.
Mariani, M., 2019. Big data and analytics in tourism and hospitality: a perspective
article. Tourism Review.
Benhlima, L., 2018. Big data management for healthcare systems: architecture, requirements,
and implementation. Advances in bioinformatics, 2018.
Gillan, C.M. and Whelan, R., 2017. What big data can do for treatment in psychiatry. Current
Opinion in Behavioral Sciences, 18, pp.34-42.
Poel, M., Meyer, E.T. and Schroeder, R., 2018. Big data for policymaking: Great
expectations, but with limited progress?. Policy & Internet, 10(3), pp.347-367.
Knoppers, B.M. and Thorogood, A.M., 2017. Ethics and big data in health. Current Opinion
in Systems Biology, 4, pp.53-57.