Information Systems and Big Data Analysis: Theory, Challenges, Methods, and Business Applications

This report discusses the theory and characteristics of big data, challenges faced by big data analytics, methods available to examine big data, and ways in which big data technology can lead businesses to better decision-making and resource allocation. The report also includes a poster on big data analytics. Subject: Information Systems. Course Code: Not mentioned. Course Name: Not mentioned. College/University: Not mentioned.

Information Systems
and Big Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................1
What is Big data and its Features.....................................................................................................1
Challenges of Big data Analytics.....................................................................................................2
Methods that are presently available to examine big data...............................................................3
How technology of big data could lead the business, an description with illustrations..................3
Poster................................................................................................................................................5
REFERENCES................................................................................................................................6

INTRODUCTION
In this report it discuss about the term of big data it is usually very big, enormous, induce
and composite. The structure of data are distinct to maintain and control the big information.
This raw structure of truths and statistics which need to executed in a tabular structure(Agrawal,
Delen and Benjamin, 2019). In the report it consists the theory and characteristics of big data.
Apart from this, there are some challenges for the technology of big data analytics they are
dealing while using it. Also, there are some methods which are present to examine the theory of
big data. At last, it explain some ways of leading the business through the technology of big data
What is Big data and its Features.
It is the structure of technology in which it utilized for keeping, examining and handling
the enormous information. This equipment is mainly utilized to determine the designs of data in
various type of areas like; gambling, protection of environment surroundings, agriculture,
medicine and The form of big data is essential. Here are some various features of big data but
some of the features are discussed as below:
 Value: This is very essential feature of big data, it is mainly assist in determining the
worth of big data along with the designs from the order of information. Which express
the outcomes of maximizing the firm performance very effectively.
 Volume: In this feature of big data, it indicates that the information is present in high
amount and it can't be possible to execute in a very simple manner. It shows some
collection of data. It mainly helps in gathering the actual raw data and figures which are
not categorized. The approach of automated data storing is a procedure of recording the
information which mainly assists to examine the detail and create feedback according to
the data.
 Velocity: The feature of big data can be define as a speed in which firm get to keep and
handle the diversified information(Astill and et.al., 2020).
 Variety: In this feature of big data it mainly depends upon the actual raw data and figures,
it can be organized, unorganized and semi-organized. The organized structure of
information is scheduled in a form of database by utilizing the comparative database
management process. The unorganized structure of information is not present in the
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structured way. Also the semi-organized structure of information is moderately scheduled
in the structured way. It also includes some diversified and variety of discrete types of
information.
Challenges of Big data Analytics.
In current scenario, each and every thing are executed with the help of technology. So, on
that basis there are some few challenges which are to be faced by the big data analytics that are
discussed below:
 Combination of data through the extent of origin: It involves some various origins of
gathering the information. The data can be gathered through the logs of customer,
financial records, reports made by workers, demonstration of emails and social media
sites(Barnes, Guo and Chan, 2022). Data combination is very essential for illuminate the
outputs and prepare the opinions on that basis.
 Lack of skills and understanding: This is one of the very big challenge for the
organizations to manage some of the technology. Then the companies required some of
the trained employees to operate that technologies. On that basis they hired professionals
fro their company which include high expenses. The hired professionals are; Data
analyst, Data engineer and Data scientist. Organizations invest high cost for hiring such
candidates who have good knowledge and professional skills of technical understanding.
 Problems in Data development: In this type of challenge companies having big amount of
information and it developed substantially. Mostly the information comes in an
inappropriate manner in reports, audio, words, statements and videos and many other
origins. At the time of arranging the data in a various form. Company need to understand
the group of information(Bellatreche and et.al., 2021). In that case, if candidate doesn't
have the appropriate knowledge of the detail. Then it create complexity to maintain the
information of backup.
 Safety of data: It is one of the most biggest challenge to secure the data of the company.
The enormous data which mainly kept on the database are unsecure and it is one of the
large benefit for the spiteful hackers. There are some spiteful software which includes
viruses, worm and trojan horse which mainly create an impact on the smooth functioning
of the organization .
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Methods that are presently available to examine big data
According to Mckinsey, there are various methods which are mainly utilize to examine
the big data. It can be discussed below:
 Mining of data: In this method of big data analysis the procedure of data extract authorize
the firm to mining the information from the bigger excavation. It is utilized to determine
designs and correlated the available bunch of information.
 A/B testing: The equipment of A/B testing assists in relating the control classification and
experimental category. In this beginning time of A/B testing, the theory are made and
variables teams it includes autonomous and parasitic variables which are to be
completed(Du and et.al., 2021). This test is executed on autonomous variables and
influence is researched on the parasitic variable.
 Statistical data: This method of big data analyses is a branch of study in which they
compare with the gathering, firm, examine, illuminate and demonstration of informative
data. The complete statistics is categorized into two important classification: descriptive
and inferential statistics. In which the descriptive statistics mainly deals with the analyses
of central tendency and the another statistics which named as inferential statistics assists
in testing the information.
 Integration and combination of information: The important goal of gathering the
information through various of origins is to examine the reconstruction of information is
to research their prospects individually. Combination of data is a procedure in which the
mixture of information to identify the judgement and create illumination on that basis.
 Handling of common language: After introducing the cloud computing and artificial
intelligence. The communication they utilize in the current generation correspond with
the normal language of a person. It mainly assist to simply know the bugs and coding
which can be simply eliminated as well(Holland, Mullins and Cunneen, 2021).
How technology of big data could lead the business, an description with
illustrations.
Technology of big data analysis give in company to estimate some few trends that are
inducing in market at current and what are the consumer (tasteHyun and et.al., 2020). Here are
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some certain ways that assist to elaborate the analysis of large information leads the company
which discussed as below:
 Bettering the goods feature: There are some technology which assist the organization
related to the big information. This is relatively simpler to better the goods and services
given by a firm. The main reason behind that it also understand where the company is
deficit and what are the various techniques that the company need to adopt.
 Proper utilization of scarce funds: It mainly assists to allocate funds that are few in nature
for better outcomes. It also give some ways for maximising the income generation and
utilize funds in such a manner that need to be prove from the better alternatives. It usually
more concentrate on utilizing the resources in such a manner that provide competitive
benefits with the help of innovative policy and plans.
 Better decision making: The collection of data assist in giving the proper guidance
regards what and how can be completed, the plans that need to subscribe in smooth
relation among firms and over the years also. It mainly assists to identify the cause that
support to waste and maximization of discarded expenses.
 Security and safety of information: It confirms that the data is maintained importantly
and secured from the discarded frauds, breach and risk of helpful information. It can be
protected through the big technology and growing approach which helps in improving the
efficient smooth running of company (Khakifirooz, Chien and Chen, 2018).
 High capable consumers: It gives data about the consumers that usually provide high
profit and outcomes in the company. It assists to give some equipments that mainly
attract the customers from the market. It also help to grow the system subscribing in
sustaining the comparative tasks and projections.
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Poster
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REFERENCES
Books and Journals
Agrawal, R., Delen, D. and Benjamin, B., 2019. Clinical intervention research with EHR a big
data analytics approach. In 25th Americas Conference on Information Systems, AMCIS
2019.
Astill, J and et.al., 2020. Smart poultry management: Smart sensors, big data, and the internet of
things. Computers and Electronics in Agriculture. 170. p.105291.
Barnes, S.J., Guo, Y. and Chan, J., 2022. Big Data analytics for sustainability: Insight through
technological innovation. Information & Management.
Bellatreche, L and et.al., 2021. Big Data Analytics: 8th International Conference, BDA 2020,
Sonepat, India, December 15–18, 2020, Proceedings (Vol. 12581). Springer Nature.
Du, J and et.al., 2021. To be or not to be: Negotiating leisure constraints with technology and
data analytics amid the COVID-19 pandemic. Leisure Studies. 40(4). pp.561-574.
Holland, C.P., Mullins, M. and Cunneen, M., 2021. Creating Ethics Guidelines for Artificial
Intelligence (AI) and Big Data Analytics: The Case of the European Consumer
Insurance Market. Available at SSRN 3808207.
Hyun, Y and et.al., 2020. Why Big Data Analytics Competency for Organizational Agility: A
View of IS Resources. In PACIS (p. 114).
Khakifirooz, M., Chien, C.F. and Chen, Y.J., 2018. Bayesian inference for mining
semiconductor manufacturing big data for yield enhancement and smart production to
empower industry 4.0. Applied Soft Computing. 68. pp.990-999.
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