Big Data Technology and its Characteristics: Challenges and Techniques for Analysis

This report discusses the characteristics of big data technology, its challenges, and techniques for analysis. It covers topics such as data volume, variety, and velocity, as well as data integration, mining, and machine learning. The report also highlights the importance of managing data complexity, security, and privacy.

Big data technology is based upon large set of data
that is based upon large set of data belonging which
relates with different customers within business.
This is important for an business to develop big
data technology which helps to make business
organization grow within particular market. An
organization developing good software helps upon
handling operations based upon big data
technology, The report is based upon explanation
over big data technology with its characteristics.
Scope of big data is wider as it tends to impact
business and its functioning. Nature is dynamic as
it makes business operate with the help of data
analysis. Further, this report focus over different
challenges that has been faced over analysing big
data and its various techniques required in order to
make analysis upon big data. In the end project
contains way within which big data technology has
been supporting business in more effective manner.
In modern world competition is high which makes
big data technology has become boom that has
impacted IT industry on large scale. The example of
Big Data technology are Hadoop, Spark, NO-SQL,
Hive and Cloud. These technologies and software
leads upon managing big data which is related to
business. The big data technology also relates with
various factors like data management and data
storage that is required for business growth of
business and helps in developing synchronization of
big data, There are mainly two types of big data
technology which makes operational and analysis
with big data technology(Singh, 2019). There are
two kinds of big data technology which is based
upon analyzing business technology in more
effective manner.
Information Systems and Big Data Analysis
INTRODUCTION Big data and its characteristics
Volume of data- In general case perspective approach
has been handling large amount of data which is used
within an organization(Singh and El-Kassar, 2019). Big
data volume is large and number of consumers is
always high in case of multinational and national
organizations. In order to handle large volume of data
an organization which is important for organization.
This make skills and trained employee is able to handle
responsibility of business by making skilled and trained
employees.
Variety of data- There are different part of data which
is based upon immense in relation over big data
technology which is important to be developed and
includes various aspects of data technology that makes
data to be analyzed in more effective way. It is required
to make sure that data has been transferred in effective
way. An organization through this is able to completed
tasks like financial management and business strategy
preparation.
Velocity of data- It is considered as the speed of data
through which it is transferred from one source to
another. In the recent times velocity of data is managed
by advanced software like HADOP HPCC in the
business. It is very much essential for a company to
manage velocity of data consistently for long term
success of business.

Techniques that are currently
available to analyse big data
Big Data technology could support
business
Challenges of big data analytic
Data integration- In this management of big data
technology is done with integration that is related
over various challenges faced by an organization.
The data integration has important role to play with
management of data over large resources.
Researcher collects data over various resource that
makes responsibility taken for facilitating data
integration. This is used for collecting data over
various sourced which has become responsibility
researcher for facilitating data integration.
Data complexity- In order to handle data
complexity it is essential for a researcher to
overcome several issues and practices (Singh,
2019). The data is complex and rigid in many cases
which makes hard for researcher to handle data.
Data complexity is a major challenge and it is
ethical duty of IT experts in a business to handle
data complexity.
Data security- The main issue and challenge in
data handling and maintenance is data security. It
is major role and responsibility of management to
handle data security with major patience in order to
manage security of data. In the world of
technology there are many attacks like malware
and spyware can impact whole data. It is important
for researcher to analyses and develop big data
while keeping mind various security issues.
Data mining- This is common tool used by an
business organization which makes handling of big
data analytic done more effectively(Siyuan, 2018).
The data mining is able to extract patterns from
large data setting over making setting and
combining methods through statistics and machine
learning within database management. There are
various kinds of aspects which is based upon
learning with development.
Machine learning- This is based over artificial
intelligence, machine learning which is based over
dimensions of computer science and algorithm. The
machine learning provided over analyzing about
various perspective.
Statistics- These are those technologies which is
based over process, manage, and analysis data is
entirely different with expensive field that is similar
and develops over time. Through techniques and
technology over size data which is valuable in
nature. Managing effectively host of business
product and market insights. This makes
organization achieve its goals effectively.
The current competitive environment is based over big data
technology that helps upon making business grow with faster
and better pace helping in facilitating organization making
development possible with data customers(Tiwari, Wee and
Daryanto, 2018). This makes business organizations develop
competitive advantage helping upon making big data
technology achieved. It has helps in supporting business in
following way which are as follows:
Management of data- Big technology helps over management
of data that has been used for developing business in more
effective way. Under big data technology software and systems
makes it easy for business over managing large amount of data.
The data has been managed by big data technology which is
based upon customer handling. For example Aston martin is an
multinational UK based car company that manages large
amount of data within various parts of glob helping in making
big data technology.
Privacy of data- The privacy of data which is important for an
organization making organization with customers by increasing
there faith. For example Astra Zeneca is required to maintain
privacy data which is done through big data analysis.

Big data technology within its application is
based upon business which is irreplaceable in nature
most of organizations in recent time using big data
technology. This is important for business which
leads upon focusing over big data which creates
long term satisfaction. In recent time challenges in
relation over bigg data has increased day by day
which makes strong need to be developed upon
analyzing over customer management. In order to
adopt challenges in relation to big data analytic
management should that developing capabilities
over taking advice of IT experts. The main
challenges that is based upon big data analytic with
management over creating depth analysis with
capabilities that has been taking advice of IT
experts.
The challenges of big data
analytic
Techniques that are currently
available to analyse big data
Data mining- This is common tool used by an business
organization which makes handling of big data analytic done
more effectively(Siyuan, 2018). The data mining is able to
extract patterns from large data setting over making setting
and combining methods through statistics and machine
learning within database management. There are various kinds
of aspects which is based upon learning with development.
Machine learning- This is based over artificial intelligence,
machine learning which is based over dimensions of computer
science and algorithm. The machine learning provided over
analyzing about various perspective. Statistics- These are
those technologies which is based over process, manage, and
analysis data is entirely different with expensive field that is
similar and develops over time. Through techniques and
technology over size data which is valuable in nature.
Managing effectively host of business product and market
insights. This makes organization achieve its goals effectively.
CONCLUSION
From the above discussion it can be
concluded that big data is large amount of data
which has been used by researcher of an
organization. Through big data technology
researcher has been helped within management of
data overlarge scale. The projects is related over
essential of researcher making challenges over come
with big data technology for dealing upon complex
data. Through report importance of big data
technology and its applications has been marked out
with faster and quick operations.
References
Books and Journals
Choi, T.M., Wallace, S.W. and Wang, Y., 2018. Big data analytics in operations management. Production and Operations Management, 27(10), pp.1868-1883.
Du, G., Liu, Z. and Lu, H., 2021. Application of innovative risk early warning mode under big data technology in Internet credit financial risk assessment. Journal of
Computational and Applied Mathematics, 386, p.113260.
Liu, Y., 2018, January. Big data technology and its analysis of application in urban intelligent transportation system. In 2018 International Conference on Intelligent
Transportation, Big Data & Smart City (ICITBS) (pp. 17-19). IEEE.