Characteristics, Challenges and Top Technologies of Big Data Analysis

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This report discusses the characteristics and challenges of Big Data Analysis, including its volume, variety, veracity, value, and velocity. It also covers the top technologies used to manage Big Data, such as Apache Hadoop, MongoDB, and Rainstorm. The report concludes with a summary of the importance of Big Data Analysis in today's business world.
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Information Systems and Big Data
Analysis
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Table of Contents
INTRODUCTION................................................................................................................................3
MAIN BODY ......................................................................................................................................3
Characteristics of Big Data .............................................................................................................3
Challenges of big Data.....................................................................................................................4
Top Technologies of big data .....................................................................................................5
CONCLUSION....................................................................................................................................6
REFERENCES.....................................................................................................................................7
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NTRODUCTION
The term Big Data is referred as the data which contains a large variety of data which is very
complex in nature. These type of data are very difficult to be managed by the traditional data
processing application software. Data having various fields offers the statistical power , while the
Data with higher complexity can also lead to the higher complexity which can lead to the fall in
discovery rate(Galetsi Katsaliaki and Kumar 2019). The Big Data is used by the organisations who
works on a large platform and have various functions which needs to be performed effectively and
efficiently. The Big Data helps the business and the organisations to organise, manage and export
the complex data in an effective manner. This report will include the various characteristics and
challenges that are related with the Big Data following by the technologies which are used by used
by the various business and organisation to manage the Big Data.
MAIN BODY
Characteristics of Big Data
Big Data is the large amount of data which is very complex to maintain in order to maintain the
effective working of the Organisation. These data are basically unstructured and not maintained
properly such as audio files. The Big Data sets are voluminous that the traditional and ineffective
method can not be opted to manage the complexity of this data. The big data is comparatively new
according to the origin of large data sets in 1960s(Kandhamma and Duraisamy 2018). Big data has
many benefits such as, it can help the business and the organisation to make it possible to gain more
and complete answers because of the availability of information. The more complete answers can
be defined as the more confidence in the present data that is available which can be helpful in
opting a different and effective approach to tackle the complex data and its management. The big
data can also help to address the various range of Business activities from customer experience to
analytics such as, product development, predictive maintenance, customer experience and fraud and
compliance. The Big Data is used by various business and organisations to process the data in
simpler and easy form. The Data has many characteristics which are as follows
Volume
The big data are considered as the large amount of data which is quite high in volume, these Data
are generated by various sources such as, newspapers, television, business process, machines, social
media platforms, networks and human interactions. The Facebook is considered as an online
platform which is used by a lot of people and it can create a large amount of data approx a billion
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messages. The big data can be helpful in the management of such data in an effective manner.
Variety
The Big data can be structured and unstructured which can be generated from various sources. The
data can be collected from databases and sheets. But nowadays the data can be in a form of PDFs,
Emails, Audio, messages, files etc (Nguyen and et.al 2018). The big data help to categorise the data
in various forms in which it can be more easy and quick to manage.
Veracity
The term veracity is referred as the accuracy of data. There are a lot of ways to filter and translate
the data. Big data is an important tool which can be helpful to manage the Data and also it can
encourage in business development.
Value
The term value is considered as an important component of big Data. The Big data is valuable and
reliable source which can be helpful to store process and analyse the Data. The big data functions in
an effective manner so that the complexities of the data can be reduced and a better and processed
data can be obtained( Bhattacharyya and Kumar 2018).
Velocity
The term velocity plays an important role as it creates the speed by which the data can be created in
the given period of time. It contains the various links of data sets speeds, rate of change and activity
bursts. The main objective of big data is to provide the demanding data in a quick way. The big data
also deals with the speed at the data which flows from sources such as application logs, business
processes etc.
Challenges of big Data
The big data challenges can be defined as the best way of handling the various amount of data
which involves the process of storing, analysing the huge set of information on different stores of
data. There are a lot of challenges which can be faced during the use of big data. The challenges are
as follows
Lack of knowledge
To use the advanced method such as big data there are a lot of skills and knowledge which is
required. The big data can be managed buy the skilled professionals such as data scientists, data
analyst and data engineers which can help to manage the data effectively and efficiently. The
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business and organisation can find it difficult to manage the data due to the lack of professionals.
Lack of proper understanding of large data
The various business and the organisation fails at the management of big data as there employees
are not effective enough to process the data. The data professionals must be knowledgable and
effective enough to know about what is going on and how the data is managed in the business and
the organisation so as to increase the efficiency.
Data growth issues
The main issue of the challenges of big data is related with the storage of these data in an accurate
manner so that the complex data can be changed in an easy form. The data sets grow in a huge
exponential which makes it more difficult to handle. The most of the data can be very complex and
unstructured to handle due to its form such as, documents, files, messages and other sources too.
This makes the form of data hard to store and difficult to manage as it continues to grow.
Top Technologies of big data
The Big Data technologies can be defined as various soft wares utility which are designed to
analyse, process and extract The information from different complex and large data which can not
be deal by the traditional data. There re a lot of big data technologies which can be used to manage
the complex data such as, Apache Hadoop which is an open source framework based on Java which
is developed by the Apache software foundation, this technology provides the excellent distribution
of storage platform and process the Big data by using the various map reduce programming model.
The next technology of Big data is the MongoDB which also an open source, cross platform and
document oriented base for data which is cesigned to store, and tackle the large amounts of data
while providing the high quality of performance. The MongoDB does not involve the storage and
the backup of data in the table format, The MongoDB is very popular due to its document oriented
technology and functional ability. There are various companies which uses MogoDB such as,
Facebook, eBay, met life and google.
The rainstorm is also a database management system that manages and analyses the Big data. The
software is developed by the rainstor company which supports the cloud storage and various other
terms such as the ability to sort the complex data into simpler form(Zhangand Dong 2021). The big
data technologies helps the business and the organisation to enable the highly efficient data
management which accelerates data analysis and queries. The also allows the data analysts to run
faster queries and also analyses by using the SQL queries map reduce. These big data technologies
have a great impact in the market and IT industries as they make the process off data storage and
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processing efficient, which is the key factor in the reduction of cost. It also helps to identify the
inefficiencies and regulates them in the best possible way by the help of big data technologies
which helps in increasing sales and revenue by shaping the products and services according to the
wants and needs of business as well as the customers.
CONCLUSION
The above report went into detail with various complex topics such as Big Data which is widely
used by the business and the organisation so that they can get an effective approach to manage,
maintain and process the complex data in the easier and simpler form. The big data is an excellent
way of analysing the data of huge volume with great efficiency and accuracy. Further more, The
various characteristics and challenges of Big data were also discussed, including the Top Big data
technologies and their uses were also highlighted so as to make it more clear and understandable.
REFERENCES
Galetsi, P., Katsaliaki, K. and Kumar, S., 2019. Values, challenges and future directions of big data
analytics in healthcare: A systematic review. Social science & medicine, 241, p.112533.
Kandhammal, K. and Duraisamy, S., 2018. REVIEW ON BIG DATA CHALLENGES FOR 4G
REVOLUTIONS. International Journal of Advanced Research in Computer Science, 10(5).
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Nguyen, V.G., Brunström, A., Grinnemo, K.J. and Taheri, J., 2018. SDN helps velocity in big data.
Santhosh Kumar, D.K. and D‘Mello, D.A., 2018, December. Strategies and challenges in big data: a
short review. In International Conference on Intelligent Systems Design and Applications (pp. 34-
47). Springer, Cham.
Verma, S., Bhattacharyya, S.S. and Kumar, S., 2018. An extension of the technology acceptance
model in the big data analytics system implementation environment. Information Processing &
Management, 54(5), pp.791-806.
Zhang, J. and Dong, L., 2021. Image monitoring and management of hot tourism destination based
on data mining technology in big data environment. Microprocessors and Microsystems, 80,
p.103515.
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