Big Data Analysis for Business Management: Techniques, Challenges, and Importance

This report explains big data analysis techniques, challenges, and importance for business management. It describes the characteristics of big data and how it can support business growth. The report includes a poster and accompanying paper on Information Systems and Big Data Analysis. The subject is Business Management, course code BMP4005.

Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Submitted by:
Name:
ID:
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Contents
Introduction p
What big data is and the characteristics of big data p
The challenges of big data analytics p
The techniques that are currently available to analyse big data
p
How Big Data technology could support business, an explanation
with examples p
Poster p
References p
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Introduction
Big data has modified into an factor in introducing growth for any enterprise.
The term is utilized to explain a crucial and massive volume of data to be proceed by
any software tool (Zhang, and et., al., 2020). It can also be refereed to as a hi tech
instrument utilized to manage huge amount of data. Big data is imperative to a
business as it generates a more accurate analysis because of huge amount of data.
Consistently users can create better decisions that can be assisting In deducting risk
and produce operational efficiencies. This report will describes about big data and big
data analytic, its characteristics and its importance in growing business.
What big data is and the characteristics of big data
A immense data velocity of data is known as big data. The huge the extent of data
bigger issues it is to manage and manipulate. Data is the utilization of advanced
analytic tools against very large diverse data sets that considers organized,
unorganized data from various sources and in varied amount from terabytes and
petabytes. It permits analysis, researchers and business users to create better and
faster decision using data that was earlier inaccessible or unusable. Enterprises can
use advance analytic tools just as text analysis , machine learning and data mining
and statistics and natural language process to add new insights from earlier
untapped data. It has some characteristics that is listed in below -
 volume - the massive volume of details are stored in secure form .
According to the structure of organization they have a huge amount of data
which is being used to keep safe from the hacker and other spies that try to
catch the data and copy them so that they can have private details of an
institution.
 variety - it can be organized , unorganized and semi organized that are
being gather from various sources. Data will only be gather from database
and sheets In the previous days, but these days the information will come
in array forms that are pdf , emails , audio and images videos many others.
 velocity - it plays an essential role in comparison to another . It makes the
speed by which the data is generated in actual time. It includes the linking
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of incoming data sets speeds, rate of modification and activity bursts. The
prime aspects of big data is to give demanding data quickly.
Companies are facing massive volumes of data but they don't have any idea to
manage this details are used by them (Yan, , and et., al., 2018). But the
opportunity exists with the right technology stages to analyze almost all of the
data. The correct technology adds a improved analysis of their business , users
and the marketplace. This tends to be the present conundrum facing current
business across all business.
The challenges of big data analytic
while gathering a data company faces a many issues that is listed in below -
 Bad quality of data - the issue with any data in any company is always that
it is hold in various places and in various structure. A easy task like
having a look at generation costs may be daunting for a manager when
finance is holding on distribution cost. Payroll and another financial data
as it must act while gathering details from machines on the production
stage .
 Data growth - one of the major issue data is security. Details is growing
function with clip and with that business are pattern to save huge
amounts of data. Most of this data is infusion from pictures. Audio , texts
and many others. That are unorganized and not in database. It is complex
to extract and determines all unorganized data. Theses are the problems of
big data structure.
 Data validation - It is on a big data scale that could be either complex.
An institution can get same sets of data from various sources but the data
from these sources may not constantly be same. Getting the details to
agree with each other and looking out for accuracy, usability and security fall
under a process known as data governance.
 Data security - safety could be one of the most intimidating massive
data issues particularly for making that have delicate details of company
or have admittance to a lot of individual user process. Assailable data is
an attractive mark for cyberattack and despite ful hackers (Osinenko,, and
et., al., 2021).
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 Big data handling cost - the management of big data have right system
of adopting stage, demands a lot of expenses . For case if the institution
selects to utilize an on site solution should be ready to consume wealth on
new instrumentality, electrical energy , new selection just as creator and
management and many more.
 Data integration - it revolves around integration from multiple business
areas into one version of truth useful to all member of the company . Thus,
the information technology team find it quite complex to manage massive
data from many various software and hardware stages and In all possible
structures.
The techniques that are currently available to analyze big
data
In order to analyze the huge data technology is getting more smart so in current era
new tools and invention has been done described in below -
 Association rule learning - it is a method for concealment involvement
correlation among variables in huge database. It was first utilized by
major super market chains to invent systems. It is utilize to assist place
products in improved approximately to each other in regards to raise
sales, extract details about visitors to websites from web server logs ,
analyze biological data to uncover new relationships.
 Genetic algorithms - it is divine by the manner evolution operations, via
mechanisms just as inheritance mutation and natural selection. these
instrumentation are utilized to evolve solutions to issues that needs
optimization. This is used to listing doctors for health facility emergency
rooms, return s mixture of the optimal materials and engineering practices
needed to improve fuel businesslike automobile (Mohapatra, and
Mohanty, , 2020)..
 Machine learning - it includes software system that can learn from data. It
provides computers the capability to learn without being explicit programs
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and is concentrate on creating assumptions on the basis of structure from
sets of training data.
 Social network analysis - it is a techniques that was first utilized in the
telecommunication industry and then rapidly implemented by sociologist
to practice interpersonal relationship it is now applied to analyze the
relations among people in many sections and commercial activity. It
presents individuals within a websites while connected shows the
dealings among an individuals.
How Big Data technology could support business, an
explanation with examples
data plays a huge role in analysis valuable insights regarding target
demographics and customers preferences. From all communication with technology
careless of whether it is progressive or resistless, they are making new data that can
explain them. With data being gathered via goods, video cameras , credit cards , cell
phones and other marks . It can change the system and small business to act
business as data aggregation and reading become more approachable and
underdeveloped cost effective technology are continuously emerge and developing
that creates it incredibly simple for any company to seamlessly executed big data
solutions. It makes the operations more convenient and ease for company to have an
effective and achievable business in marketplace. It assist in having a relevant details
that can be useful for company . This is an effective business that should be an
initiative that is being adopted to organize the company details to keep them private
and personal. It have a benefits that are as :-
 It gives business the instruments they requires to make impressive decision
that are on the basis of data not assumed or having correct observation.
This states data must be no longer be the sole domain of IT departments.
 It helps In understanding the users in order to make them a loyal users of
the company. This is being initiative that satisfies the users through various
sources it also help in organizing data in a systematic form.
 It helps in developing business activity, as like concern have they increase
the productivity and collects the good and improved details that is beneficial
for company to run a business (Song, and et., al., 2020) .
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Poster
Paste your digital poster here
References
Jiang, D., and et., al., 2019. Big data analysis based network behavior insight of cellular
networks for industry 4.0 applications. IEEE Transactions on Industrial
Informatics, 16(2), pp.1310-1320.
Izquierdo, J.L.,and et., al., 2021. Clinical management of COPD in a real-world setting.
A big data analysis. Archivos de Bronconeumología (English Edition), 57(2),
pp.94-100.
Khalid, Z.M. and Zeebaree, S.R., 2021. Big data analysis for data visualization: A review.
International Journal of Science and Business, 5(2), pp.64-75.
Hou, R., Kong, Y., Cai, B. and Liu, H., 2020. Unstructured big data analysis algorithm and
simulation of Internet of Things based on machine learning. Neural Computing and
Applications, 32(10), pp.5399-5407.
Zhang, W., and et., al., 2020. Multimodel feature reinforcement framework using Moore–
Penrose inverse for big data analysis. IEEE Transactions on Neural Networks and
Learning Systems, 32(11), pp.5008-5021.
Yan, X., and et., al., 2018. Energy-efficient shipping: An application of big data analysis for
optimizing engine speed of inland ships considering multiple environmental factors.
Ocean Engineering, 169, pp.457-468.
Osinenko, P., and et., al., 2021. Application of non-destructive sensors and big data
analysis to predict physiological storage disorders and fruit firmness in
‘Braeburn’apples. Computers and Electronics in Agriculture, 183, p.106015.
Mohapatra, S.K. and Mohanty, M.N., 2020. Big data analysis and classification of biomedical
signal using random forest algorithm. In New Paradigm In Decision Science And
Management (pp. 217-224). Springer, Singapore.
Song, J., and et., al., 2020. Social big data analysis of future signals for bullying in South
Korea: Application of general strain theory. Telematics and Informatics, 54,
p.101472.
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