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

This report discusses the meaning and characteristics of big data, challenges faced by organizations in big data analytics, and techniques available for analyzing big data. It also explores how big data technology can support businesses in making better decisions, understanding customers, delivering smart services and products, and improving business operations.

Information Systems
and Big Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................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, please use examples wherever necessary........7
CONCLUSION................................................................................................................................8
Poster................................................................................................................................................8
REFERENCES..............................................................................................................................10

INTRODUCTION
An information system is a construction that collects, processes and distributes
information. This system is based on people and computers that processes the information. A
data and correspondence innovation was utilized by association and the manners in which
individuals interface with innovatio (Mohapatra, 2021). Companies rely on information systems
to carry out their operations. It enables the businesses in taking part with clients and vendors.
Organisational supply chain also runs on this system. This report focuses at the large information
and the highlights of massive information, challenges regarded by way of huge facts examination
and the processes to dissect the huge facts and how massive records innovation help groups.
TASK
What big data is and the characteristics of big data?
Meaning of big data:-
Big data comprise of Big collection of statistics and it's far tricky to oversee by using
conventional strategies. It is an accumulation of prepared and unstructured records this is
assembled through organizations. These information utilized by associations to address their
business troubles that they cannot execute prior. By using the big data organisations improves the
customer service. Huge amount of data is generated by users but it is not the humans who are
creating it(Li and et. al., 2021). The example of big data is new york stock exchange that
generate change information of one terabyte every day. Organizations can likewise use outdoor
records for taking decisions. The big data are of three types: Structured, semi-structured and
unstructured.
Characteristics of big data:-
 Volume:- Volume alludes to the dimensions of statistics. It assumes a sizeable element in
deciding the worth out of records. Determined data is dealt with as huge information or
not is concern to the extent of facts. The information that is reachable to businesses is
growing step by step and the dealing with declines. New technology has been used by
businesses to cope up with this problem(King and Wang, 2021). The information is yield
from numerous beginning points, as an example, commercial enterprise tactics, reference
to people companies, correspondence framework, social media etc.

 Variety:- The data that is collected from different sources can be structured, semi-
structured and unstructured. In the earlier times information became assembled from
statistics bases and sheets yet,in present times it can be collected from PDF, Mails, photos
and videos etc.
 Velocity:- Velocity alludes to the speed of formation of information. How quick facts is
created and what quantity of time does it require to oversee records. Speed manages pace
at which records comes from sources like companies, social locations, techniques and so
on. The flow of information is uninterrupted and is really big.
 Veracity:- Veracity refers to the unwavering satisfactory of records. It is the interest of
coping with the facts productively. The maximum records that is gathered from various
sources is unorganized and to use the information in operations it's far vital to sift thru the
useless statistics
 Value:- This is The maximum fundamental characteristics of big statistics. The data that
is created should be dependable no matter how fast it is generated. If the information is
not accurate then it is not possible to store it and the information which is good is ready
for processing(Mittal and et. al., 2021). Only valuable and reliable data used for
processing and stored. Specialised individual initial believer the facts into statistics and
theoretical the precious data from it
The challenges of big data analytics; and the techniques that are currently available to
analysis big data
Challenges of big data analytics
Every organisation needs the information and it is the necessity of businesses. Companies
cannot perform its role without information. Business transactions creates information every
seconds. Analysis of Statistics need to be essential to enhance the dynamic interplay. There are
difficulties which can be seemed by way of groups. These difficulties are as follows:-
 Lack of knowledge professionals:- To manage modern technology and large data tools
organisations needs highly skilled professionals. This carries records exam, architects and
researchers. These peoples works with data sets and tools. Organisation faces the
challenge of lack of massive data professionals(Liu, 2021). Professionals have not
evolved with time but the data handling tools have developed.

 Lack of proper understanding of massive data:- Due to lack of proper understanding
of large data companies have failed to understand the big data. Employees of the
organisation has barely any familiarity with the statistics, the way to store it and what is
its significance and resources. Just specialists knows about the data and other peoples
don't know. It is impossible for employees to keep it safe if they don't know the
importance storage. When the information is needed it cannot be recovered easily as the
data is not stored properly.
 Data growth issues:- Properly putting away of splendid preparations of statistics is the
precept undertaking for institutions. The amount of records stores in server farms
maintains to increment with time very fast and it is very difficult to handle it. Most of the
information is unstructured and comes from documents, pictures, text files, and from
other locations.
 Confusion in big data tool determination:- Companies gets confused while
determining the tool for data analysis. This may result in improper selection of
technology and takes bad decisions and it may consequence in wastage of efforts, time
and money. Confusion created bad decisions and it leads the whole organisation to suffer.
Proper selection of a tool is big task and it needs full concentration to select proper tools
otherwise organisation has to suffer from bad decisions.
 Combining data from a spread of sources:- Information is comprised of numerous
sources like virtual amusement, ERP application, purchaser logs and so forth. Making
reports require integration of all tasks which is very difficult. Information incorporation is
basic for examination and announcing. As records comes from diverse sources, it calls for
numerous strategies to coordinate it which is a difficult task.
 Securing data:- It is a challenging for organisation to secure huge data. Organisation
does not engage in securing the huge data rather they engaged in understanding, storing,
examining it. The main target for hackers is big data. Organizations accept as true with
that there gift techniques for coverage is ok for purchasing facts. This isn't always the
admirable sentiment as unreliable information will become justification for vindictive
programmers.
 Organisational resistance:- Humans may be big issue for the big data and not the
technology. Big data provides the various possibilities to do the task in different

manner(Sarmento and et. al., 2021). It is difficult for the organisation to change.
Insufficient hierarchical plan, nonappearance of middle management securing and lack of
understanding are the obstruction within the affiliation.
Techniques available for analysis of big data:-
 A/B testing:- This method appears on the benchmark corporations with an assortment of
take a look at bunches to understand what consideration and adjustment will improves the
given points. Large statistics can again squeezes into this version as it can check giant
numbers. Assuming that the gatherings are of large length and to gather extensive
experience this have to locate achievement. This strategy is treasured whilst clients are
searching for after in net based totally consists of and receives fulfilled. Large digital
amusement stages like Facebook, linkdin makes use of this method to make the enjoy of
individual fruitful.
 Monte Carlo simulation:- It is an digital approach and in this fashions are made from
available effects and their probability conveyance. It includes the scope of feasible results
and decides how every specific final results will be realized(Anuar and et. al., 2021). This
method is used by data analysts to lead advance gamble examination which allows them
to gauge higher what is going to arise in future and go along with alternatives correctly.
 Machine learning:- This technique is moreover applied for investigating information. It
works with calculations to make anticipation in light of facts. It supply expectancies that
is hard to human beings to have a look at it. It additionally consists of programming
which could gains from facts. This techniques helps in differentiating amongst spam and
non junk mail email messages. It makes recommendations based on the information and
also helps in learning user preferences. This decides the chance of accomplishment for a
case.
 Associate rule learning:- This alludes to locating intriguing connections among's
elements on the subject of large affiliation. This method is utilized in keeping apart facts
about visitors who visits web sites, vicinity items in higher location to increment offers,
oversee framework logs to song down interlopers and look into herbal facts to expose
new relationships.

 Regression analysis:- This refers to Impacting a few loose factors to perceive how it
influence the other variables. It is the rate of change in one variable when other variable
change. This method works better with consistent data like pace, age or weight. This is
utilized to look at what consumer loyalty manner for customer reliability.
 Social network analysis:- This technique was used by telecom industry what's greater,
later on it changed into received by way of humanist to pay attention on friendly
connection. This process is presently used to have a look at connection among human
beings in one-of-a-kind fields and enterprise sports. There are sorts of business
enterprise: Nodes and ties. Hubs represents character with an agency additionally, ties
address connection among people. Social need of a set of customers is analysed by this
method.
How Big Data technology could support business, please use examples
wherever necessary.
 Making better business decisions:- Big data gives the equipment that are required with
the aid of corporations to pursue the alternatives better. Everyone in the organisation
should have approach to the information to improve the decision making ability(Song and
et. al., 2021). Users should be gifted to explore information with the aim that they can
answer the commercial enterprise questions. The example of this is Walmart. It provides
the data approach In a controlled manner. It has a bistro in which the organizations
throughout the complete association are welcome to carry the issues to the research
professionals and find their answers.
 Understanding the customers:- To serve the customers better organisation needs to
understand it. For example Disney is collaborating in big information because it
comprehends the manner of behaving of site visitors on the enjoyment park with the
intention that it may provide mystical encounters to them. The company presents the
wizardry band which acts as ID, entry pass, payment services and room keys. The
visitors have to swipe the band at sensors to enter into hotel or doing any activity.
 Delivering smart services and products:- If the company knows about its customers
then only it can design the products/services accordingly. Big information is using by
royal bank of Scotland to offer advanced varieties of assistance to its customers. In the

occasion that the association know approximately its customers, nobody but they could
supply clever items and administrations to its customers.
 Improved business operations:- Big data helps the companies in improving the business
operations. Businesses handle its customers properly if big data is widely implemented. It
also help the corporations in successful waste administration framework. Squander
consumes huge part of business property and with the help of tremendous facts
associations can work on their waste administration operation.

CONCLUSION
From the above report it has been concluded that big data is dynamic in nature. It truly
affects the commercial enterprise factor of view of client primarily based and item based. It is
also used by legislatures to offer financially savvy kinds of help to public. Data spreads all
around the area and to deal with that in a powerful manner businesses rely upon the statistics
systems. Information systems helps the organisation in solving their problems in effective
manner as the businesses have large amount of data. To interact with friends through social sites,
individual should also rely on information systems. This system assists the association with
overseeing records surely to perform the dreams. This report additionally centers around positive
factors of huge records, demanding situations appeared via huge statistics examination and the
procedures reachable to pay attention on massive facts and the way massive statistics innovation
support businesses.

Poster

REFERENCES
Books and Journals
Mohapatra, S., 2021. Human and computer interaction in information system design for
managing business. Information Systems and e-Business Management, 19(1), pp.1-11.
Li, H. and et. al., 2021. Understanding information security policy violation from a situational
action perspective. Journal of the Association for Information Systems, 22(3), p.5.
King, K.K. and Wang, B., 2021. Diffusion of real versus misinformation during a crisis event: A
big data-driven approach. International Journal of Information Management, p.102390.
Mittal, V. and et. al., 2021. Big Data Technologies: A Comprehensive Survey. Inventive
Communication and Computational Technologies, pp.103-114.
Liu, Z., 2021, September. Research on the construction of big data management system in the
whole process of prefabricated buildings. In 2021 2nd International Conference on Big
Data & Artificial Intelligence & Software Engineering (ICBASE) (pp. 662-665). IEEE.
Sarmento, A.G. and et. al., 2021. Applying big data analytics in DDos forensics: challenges and
opportunities. In Cybersecurity, Privacy and Freedom Protection in the Connected
World (pp. 235-252). Springer, Cham.
Anuar, N.K. and et. al., 2021, October. A Review on Privacy-Preserving Techniques in Data
Analytics. In 2021 IEEE 6th International Conference on Signal and Image Processing
(ICSIP) (pp. 1048-1052). IEEE.
Song, H. and et. al., 2021. Big data analytics in digital platforms: how do financial service
providers customise supply chain finance?. International Journal of Operations &
Production Management.