Big Data Technology: Challenges, Analytics & Business Support Analysis

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Big Data
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Table of Contents
INTRODUCTION ..........................................................................................................................3
MAIN BODY...................................................................................................................................4
A brief overview of big data...................................................................................................4
Characteristics of big data......................................................................................................4
The challenges of big data analytics and techniques available to analyse big data...............5
Big data technology could support business by using examples............................................6
CONCLUSION ...............................................................................................................................8
REFERENCES................................................................................................................................9
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INTRODUCTION
Big data technology is considered as large set of data belonging to different customers in
a business. It is essential and compulsory for a business to maintain big data technology in order
to grow at marketplace (Choi, 2018). A company has to develop good software for handling
major operations related to big data technology. In this report there is a precise explanation of
big data technology along with its characteristics. This report contains explanation of various
challenges that are effective in analysing big data and various techniques available to analyse big
data. This project also contains the way in which big data technology can support a business.
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MAIN BODY
A brief overview of big data
In today's competitive world big data technology is emerging with a boom that is creating
a huge impact on IT industry. The example of Big Data technology are Hadoop, Spark, NO-
SQL, Hive and Cloud. These technological software helps in storing and managing big data
related to a business. The big data technology also includes assessment of various factors that
like data management and data storage that are essential for growth of a business and develops
synchronisation of big data. There are majorly two types of big data technologies which are
operational and analytical big data technology (Du, 2021). It is main work of IT department in a
company to analyse and store big data in a precise way to support company operations. Big data
technology is also helpful in increasing the level of safe operations which are essential for a
business to develop big data related operations. The big data technology is considered as major
step which is essential for protecting crucial data related to customers. In the success of a
company at the marketplace big data technology play a crucial role by giving priority to large
data management in a precise manner.
Characteristics of big data
It is essential for a company to identify various factors that are related to big data
technology in order to accomplish success at the marketplace. The major characteristics of big
data technology are mentioned below:
Volume of data- In general case related scenario, it is essential for a company to develop
precise approach in handling large amount of data. Big data's volume is large and number
of consumers is always high in case of multinational and national companies. In order to
handle large volume of data which is essential for a company it is major responsibility of
a business to hire skilled and trained employees.
Variety of data- The variety of data is immense in case of big data technology which is
essential to be maintained in an effective manner it includes categories of data (Liu,
2018). In order to make sure that the variety of data is transferred in a precise manner, a
company has to do various tasks like financial management and business strategy
preparation.
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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.
The challenges of big data analytics and techniques available to analyse big data
Big data technology and its application in a business is irreplaceable in nature, most of
the companies in recent times use big data technology. It is important for a business to focus on
big data for long term customer satisfaction (Singh, 2019). In the recent times challenges related
to big data are increasing day by day so there is a strong need for data analysis in order to
manage customer data. In order to tackle challenges related to big data analytics the management
should create an in depth analysis of capabilities by taking advice of IT experts. The main
challenges in big data analytics are mentioned below:
Data integration- In the management of big data technology data data integration is
considered as a major challenge. The data integration play a crucial role in managing data
from large number of sources. A researcher collects data from many sources and it
becomes major responsibility of a researcher to facilitate 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 analyse and develop big data while keeping mind various security issues.
The techniques available to analyse big data are mentioned below:
Data mining- The data mining is a common tool used by a business to handle big data
analytics. The data mining extracts patterns from large data set combining methods from
statistics and machine learning within the database management.
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Machine learning- This message is related to artificial intelligence, machine learning is
mainly related with the dimensions computer science and algorithms. The machine
learning also provides various analysis that are based on various perspectives.
Statistics- The technologies that process, manage, and analyse this data are of an entirely
different and expansive field, that similarly evolves and develops over time. Techniques
and technologies aside, any form or size of data is valuable. Managed accurately and
effectively, it can reveal a host of business, product, and market insights
Big data technology could support business by using examples
In current competitive environment the big data technology helps a business to grow at a
faster pace by facilitating a company in handling precise data of customers (Siyuan, 2018). Many
business organisation can develop competitive advantage with the help of big data technology.
The big data technology is helpful in supporting a business with the help of following factors:
Management of data- Big data technology helps in management of data which is useful
for the business in a systematic manner. In big data technology use of advanced software
and systems makes it easy for business to manage large amount of data. The data which
is managed by big data technology, is available for a business for a long time which helps
in customer handling. For example, Morris Garages is a multinational UK based car
company which precisely manages large amount of data in different parts of globe with
the help of big data technology.
Privacy of data- The privacy of data is also important for both company and customers
in a major sense. Use and application of big data technology play a major role in business
development by maintaining privacy of data of customers. This increases faith of
customers by maintaining privacy of large amount of data. For example, Astra Zeneca
which is a British multinational pharmaceutical company maintains privacy of data with
the help of big data technology.
Customer engagement- The customer engagement is also facilitated by big data
technology as it helps in synchronisation of data. It is major responsibility of IT
department in a business to manage data according to number of customers (Tiwari,
2018). Customer engagement is top priority of every business, so big data technology
helps in increasing value of business by increasing customer satisfaction as it develops
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customer's trust in a business. Tesco which is a British multinational retail company
achieves customer engagement and satisfaction with the help of big data technology.
Business development and growth- In the market, achievement of business goals and
objectives is main target of every business organisation. With the help of big data
technology, business development and growth is achieved by a business in a set period of
time. Example, Amazon which is an American e-commerce market player achieves
majority of targets with the help of big data technology in international market.
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CONCLUSION
From the above stated report it can be concluded that big data is a large amount of data of
users which is useful for a researcher and organisation. The big data technology helps a
researcher or organisation to manage huge amount of data using appropriate technology
methods. This project concludes that it is essential for a researcher to overcome various
challenges that are associated with the big data technology to deal with complex data. This report
also concludes the importance of big data technology and its application in a business for faster
and quick operations.
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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.
Singh, N., 2019. Big data technology: developments in current research and emerging
landscape. Enterprise Information Systems, 13(6), pp.801-831.
Singh, S.K. and El-Kassar, A.N., 2019. Role of big data analytics in developing sustainable
capabilities. Journal of cleaner production, 213, pp.1264-1273.
Siyuan, F.E.I., 2018, January. Overview of application of big data technology in power
distribution system. In Proceedings of the CSEE (Vol. 38, No. 1, pp. 85-96).
Tiwari, S., Wee, H.M. and Daryanto, Y., 2018. Big data analytics in supply chain management
between 2010 and 2016: Insights to industries. Computers & Industrial Engineering, 115,
pp.319-330.
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