Information Systems & Big Data: Characteristics, Challenges & Support

This report provides a comprehensive overview of big data analysis within information systems. It defines big data and its key characteristics, including volume, variety, velocity, variability, and veracity. The report identifies several challenges in big data analytics, such as poor data quality and the use of outdated technology, and discusses techniques like A/B testing, classification, statement analysis, and social network analysis to address these challenges. Furthermore, it explores how big data technology can support businesses through improved communication with consumers, re-manufacturing of products based on feedback, risk analysis, and enhanced data security. The report concludes that big data is a crucial tool for understanding consumer needs, improving company performance, and fostering growth and development.

Information Systems and Big
Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................2
MAIN BODY...................................................................................................................................3
What big data is and the characteristics of big data....................................................................3
The challenges of big data analytics and the techniques that are currently available to analysis big data 4
How big data technology could support business.......................................................................5
CONCLUSION................................................................................................................................6
References:.......................................................................................................................................6
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INTRODUCTION
Information system can be defined as a group of unified constituents through which the information or data is collected, assimilated
and stored by the organization in an effective way. It basically helps in providing details about the products and services to the
consumers. It is a time saving process through which the clients can gather the important details related to the organization. For
example- what kind of services they provide, what type of goods are manufactured by a particular industry and many more (Ye, Zheng
and Tu, 2020). Big data analysis is a process by which the business enterprises can evaluate and upload the required amount of
information on their site. It also assists in simplifying the complex data in an efficient manner. The following report explains about big
data and its characteristics along with the challenges that are faced while using big data. It also covers the various techniques that are
accessible in order to analyse big data. Further, it also explains the importance of big data in supporting the businesses.
MAIN BODY
What big data is and the characteristics of big data
It is not easy to store large amount of information on different platforms. In order to gather required information and to provide details
about the organization, business structures need to find a single program through which they gather the details regarding market
demands. They are also required to upload the data of their performance as well as the variety of products in which it deals. That could
be done by big data. It is not necessary that the information that is being stored on big data will always be in a structured form but it
ensures easy accessibility to the information for both the clients and the business organizations(Li, et.al, 2020). It saves time and energy.
It is a quick source of collecting data along with information system. It also helps in enhancing the performance of the organization so
that they can carry their functions efficiently. Big data can also be said as a stock of variety of information in which it manages large
amount of data and other details by ensuring high speed surfing.
There are different characteristics possessed by big data-
 Volume- information that possessed large quantity of data and other details can be stored on big data very easily. Earlier there
was no single program that was designed which can assimilate high volume data, statistics and other related information about
the organization. Now, by using such an effortless platform, companies can identify the preferences of the customers by asking
for their feedbacks on the sites.

 Variety- big data is able to collect variety of data in an organized and unorganized manner. Earlier organizations need to
worry about the space which is required to accumulate the information. As, before adopting big data program, business
structures use spreadsheets, databases that are functioned by certain applications. It is much more time consuming and do not
possessed flexibility. At present, there are different sources through which information can be accessed such as, audio, videos,
mails, pdf s, images, etc. Now this could be done by big data in a prominent manner.
 Velocity- it relates with the speed by which the information and data can be surfed on the internet(Dou, 2020). Big data ensures
quick and speedy finding of necessary information for the clients and the organization so that the time and energy both can be
saved. It not only important to provide right amount of information but it is also essential to keep up with the pace.
 Variability- organizations are required to be consistent enough while providing any sort of information to the users of their
products and services. This could be maintained with the help of big data that reduces the unevenness while rendering any
information or details to anyone. It is very crucial that the companies must be regular with the flow of data and other related
details. Big data platform ensures that the information could be stored at once and just an upgradation is needed on regular
intervals by the business organizations.
 Veracity- it relates with the credibility and quality of information. Big data might have unstructured form of data but they all
are well equipped with accuracy and quality. There is no compromise done with the selection of any information. The
information stored on big data is high in volume but there is no question on the accuracy of the data.
The challenges of big data analytics and the techniques that are currently available to analysis big data
There are different hindrances that are being faced while evaluating big data-
 Poor quality of data source- the information that is being uploaded on big data should be correct and free from any kind of
error. It must not remain unfinished. As, such information produces low quality results that directly affects the credibility of
the provided platform of big data.
 Use of outdated technology- it is important to focus on technological advancements in the field of any type of business. As,
big data runs on a software that is fully advanced and new. The employees should be able to access required information and
for the same it is crucial to avoid the use of obsolete technology(Chen, Lin and Wu, 2020).
 Sharing of information- in order to share the information with large number of people, it is essential to develop appropriate
data systematically. Big data also allows unstructured information but that would become more difficult to access such kind of

subject matter. Details that are shared with the clients and the outside world requires organized form of work in order to avoid
any sort of discrepancies.
Different methods are available by which big data can be analysed in an effective way-
 A/B Testing- this technique helps in streaming the information between the employer and the employees in order to achieve
the desired goal. For this, there must be a balance that is required to be formed in sharing right information so that it could be
used efficiently by the clients.
 Classification- different categories should be made while storing any kind of information on big data platform. This would
help in reducing any confusion among the consumers. For example- information regarding various products and services in a
different category, company's formation in different category, its financial statement in another category, etc.
 Analysis of statement- companies are required to maintain a particular statement in which each and every thing is mentioned
in a detailed format. The target market, consumer base, sales margin, etc. It ultimately helps in collecting information without
losing focus(Chen and Metawa, 2020).
 Analysis of social network- it is important to understand that what kind of relation a particular company is sharing with the
consumers. It could be done by evaluating the social structure of the customers. Accordingly, information are being uploaded
on big data.
How big data technology could support business
 Communication with consumers- consumers nowadays have become more aware and specific in terms of their choices and
preferences while selecting any product or service. For this, it is important for the business organizations to understand the
thought process of the consumers so that they can gather better knowledge regarding their demands. This could be done by
promoting their brands on various social media platforms. This will also assist in reaching the right type of customers who
really need that good or service.
 Re manufacturing products- with the help of big data, companies are now able to receive the feedbacks of the consumers
which they list on the websites after experiencing the quality of the product. Along with this, the business enterprises can make
certain modifications in their products by analysing the weak areas(Elhoseny, et.al, 2018). This would lead to the growth and
development of the company by enhancing the productivity and sales.

 Analysis of risk- the business organizations can evaluate the risk factors which are present in the market and could lay adverse
effect on the company. Big data information helps in knowing the competition which is currently existing in the market. And
accordingly, the quality of the product or service of a particular business brand can be improvised.
 Safe and secure data- big data is well equipped with all sort of safety measures that provides security to the stored
information so that no one can make negative use of the available data. And it is recommended for the organizations to use anti
viruses and other advanced software in order to ensure safety(Zhang, Huang and Bompard, 2018).
CONCLUSION
The conclusion drawn from the above report is that big data is a platform that stores high amount of information on the information
system. It is said to be one of the most efficient tool that assists in the further growth and development. Information that is being
stored with big data helps the business enterprises to understand the needs and preferences of the consumers in the market. It also
helps to improvise the performance of the company by drawing its focus on the weaken areas which they are able to know after
analysing the response of the customers regarding their product or service. It also discusses about the characteristics of big data,
challenges that are faced by the organizations while evaluating big data. It also explains various methods that are available to analyse
big data. It also provides the ways in which it supports business organizations.
References:
Ye, Z., Zheng, J. and Tu, R., 2020. Network evolution analysis of e-business entrepreneurship: big data analysis based on taobao
intelligent information system. Information Systems and e-Business Management, 18(4), pp.665-679.
Li, K., et.al, 2020, April. Security Management System Construction of Information System Based on Big Data Analysis. In 2020
International Conference on Urban Engineering and Management Science (ICUEMS) (pp. 546-549). IEEE.
Dou, X., 2020. Big data and smart aviation information management system. Cogent Business & Management, 7(1), p.1766736.
Chen, P.T., Lin, C.L. and Wu, W.N., 2020. Big data management in healthcare: Adoption challenges and implications. International
Journal of Information Management, 53, p.102078.

Chen, X. and Metawa, N., 2020. Enterprise financial management information system based on cloud computing in big data
environment. Journal of Intelligent & Fuzzy Systems, 39(4), pp.5223-5232.
Elhoseny, H.,et.al, 2018, February. A framework for big data analysis in smart cities. In International conference on advanced
machine learning technologies and applications (pp. 405-414). Springer, Cham.
Zhang, Y., Huang, T. and Bompard, E.F., 2018. Big data analytics in smart grids: a review. Energy informatics, 1(1), pp.1-24.
Poster