BMP4005 - Big Data Analysis: Impact on Business Functioning
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This report provides a comprehensive analysis of big data and its impact on business organizations. It begins with a description of big data and its key characteristics, including variety, volume, and velocity. The report then delves into the challenges associated with big data analytics, such as data integration and complexity. Key tools and techniques for assessing and evaluating big data, including machine learning, statistics, and data mining, are discussed. Furthermore, the report examines how big data technology can impact organizational functioning, highlighting benefits like improved customer data management, enhanced privacy and cybersecurity, and support for business development and expansion. The report concludes by emphasizing the importance of addressing big data challenges and leveraging IT professionals to formulate best business practices for effective big data management.

Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Submitted by:
Name:
ID:
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Submitted by:
Name:
ID:
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Table of Contents
INTRODUCTION ..........................................................................................................................3
TASK ..............................................................................................................................................4
A short description of big data and its different characteristics.............................................4
Key challenges in big data analytic........................................................................................5
Key tools and techniques which are available to briefly assess and evaluate big data .........6
The way big data technology can impact on functioning of an organisation ........................6
CONCLUSION ...............................................................................................................................7
REFERENCES................................................................................................................................8
INTRODUCTION ..........................................................................................................................3
TASK ..............................................................................................................................................4
A short description of big data and its different characteristics.............................................4
Key challenges in big data analytic........................................................................................5
Key tools and techniques which are available to briefly assess and evaluate big data .........6
The way big data technology can impact on functioning of an organisation ........................6
CONCLUSION ...............................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
Big data is considered as key approach in maintaining large amount of data of key
customers (Ahsan, and Bais, 2017). In the functioning of a business, it is main and ethical duty
of management to focus on development of key operations related to big data in order to serve
demands and needs of the customers in a well defined manner. The big data technology is
considered as a key IT tool which helps the business entity to manage large database of
customers. The big data technology is supportive for a business in enhancement of its
competitive strength. In order to manage big data, it is essential for a business to include key IT
professionals in majority of operations. This project will include a description of big data and its
characteristics. Challenges and issues which are related to the big data are also considered in this
project. This project will also focus on various techniques which are available to analyse the big
data along with analysis of the big data technology can develop a business entity.
Big data is considered as key approach in maintaining large amount of data of key
customers (Ahsan, and Bais, 2017). In the functioning of a business, it is main and ethical duty
of management to focus on development of key operations related to big data in order to serve
demands and needs of the customers in a well defined manner. The big data technology is
considered as a key IT tool which helps the business entity to manage large database of
customers. The big data technology is supportive for a business in enhancement of its
competitive strength. In order to manage big data, it is essential for a business to include key IT
professionals in majority of operations. This project will include a description of big data and its
characteristics. Challenges and issues which are related to the big data are also considered in this
project. This project will also focus on various techniques which are available to analyse the big
data along with analysis of the big data technology can develop a business entity.
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TASK
A short description of big data and its different characteristics
In the modern competitive world, IT based practices are considered as key approach in
management of big data and its dimensions. In the recent times, due to increased competition
between companies, it is essential to focus on development of a methodology which helps in
maintaining big data. The key business organisations in the global and domestic marketplace are
focusing on big data technology in order to perform operations according to large database of
customers (Alharthi, Krotov, and Bowman, 2017). The big data technology is also a major
approach which uses key technological tools like Spark, Hadoop, NQ-SQL, cloud and Hive.
With the help and support of big data technology, management and synchronization of data are
also facilitated. The big data technology tools and techniques are also helpful in increasing the
chances of maintaining relationship with customers as their data is stored in a major sense. In the
functioning of a business information and technology department plays an important role in
managing big data. Key role of a business is to focus on application of big data technology based
tools with the help of IT professionals in order to set up best business practices. In order to save
the private information of customers, it is essential for the business entity to set up a major and
effective approach with the support of maintaining high profile data.
The main characteristics of big data are mentioned below:
Variety of data- In the application of managing big data, the variety of data is essential
to be taken into consideration by IT management. As there is a presence of large number
of customers, there are several types of nature and data which are stored. In order to
develop effective methodology in managing variety of data, it is important for the
business to use precise data management tools (Karim, Siddiqa, and Imran, 2020). The
financial variety of information of key customers and its storage is also supported of big
data technology based tools and techniques.
Volume of data- In the big data technology, there is generally huge amount of data
which needs to be properly management. Having a major volume of data, is also one of
the main characteristics of big data. The data which is available in high volume is
essential to be stored and managed with the help of advanced IT methods.
A short description of big data and its different characteristics
In the modern competitive world, IT based practices are considered as key approach in
management of big data and its dimensions. In the recent times, due to increased competition
between companies, it is essential to focus on development of a methodology which helps in
maintaining big data. The key business organisations in the global and domestic marketplace are
focusing on big data technology in order to perform operations according to large database of
customers (Alharthi, Krotov, and Bowman, 2017). The big data technology is also a major
approach which uses key technological tools like Spark, Hadoop, NQ-SQL, cloud and Hive.
With the help and support of big data technology, management and synchronization of data are
also facilitated. The big data technology tools and techniques are also helpful in increasing the
chances of maintaining relationship with customers as their data is stored in a major sense. In the
functioning of a business information and technology department plays an important role in
managing big data. Key role of a business is to focus on application of big data technology based
tools with the help of IT professionals in order to set up best business practices. In order to save
the private information of customers, it is essential for the business entity to set up a major and
effective approach with the support of maintaining high profile data.
The main characteristics of big data are mentioned below:
Variety of data- In the application of managing big data, the variety of data is essential
to be taken into consideration by IT management. As there is a presence of large number
of customers, there are several types of nature and data which are stored. In order to
develop effective methodology in managing variety of data, it is important for the
business to use precise data management tools (Karim, Siddiqa, and Imran, 2020). The
financial variety of information of key customers and its storage is also supported of big
data technology based tools and techniques.
Volume of data- In the big data technology, there is generally huge amount of data
which needs to be properly management. Having a major volume of data, is also one of
the main characteristics of big data. The data which is available in high volume is
essential to be stored and managed with the help of advanced IT methods.
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Velocity of data- The velocity of data is termed as the speed through the big data is
transferred from one source to another (Manogaran, Shakeel, and Muthu, 2020). The
velocity of data is considered as key approach in management of data with the help of
major software like HPCC and HADOP. The velocity of data should be measured by a
business and it is also essential
Key challenges in big data analytic
The big data technology analytic approach face crucial challenges which are essential to
be managed and eliminated in order to manage key operations of a business. The technology in
big data is now widely used in various international and national companies to provide support to
key operations of the company. It is key role of a business to focus on dealing with major issues
and challenges related to big data in order to lead the competition. The big data analytic
challenges must be handled by information and technology and research and development
department of a business in order to gain expected results (Mittal, 2020). This is also one of the
key role of a business to focus on analysing the situation and take essential actions in order to
deal with the same. The major challenges in the field of big data technology are mentioned
below:
Integration of big data- It is one of the most crucial challenges in big data analytic
which states that integration of data is hard and necessary. Big data integration should be
done while taking into account application of systematic tools which done by data
analytic. It is essential for the business to focus on integration of big data in order to gain
competitive advantage (Nair, 2020). The integration of big data should be developed by a
researcher in order to increase then potential of business while managing customer
database.
Complex data- The data complexity is considered as one of the key issues in the field of
data management and analytic (Roh, Heo, and Whang, 2019). The complexity in data
creates a rigidity for the researcher that makes hard for data to be understood.
Arrangement of data is also essential for the researcher in order to develop a systematic
approach.
transferred from one source to another (Manogaran, Shakeel, and Muthu, 2020). The
velocity of data is considered as key approach in management of data with the help of
major software like HPCC and HADOP. The velocity of data should be measured by a
business and it is also essential
Key challenges in big data analytic
The big data technology analytic approach face crucial challenges which are essential to
be managed and eliminated in order to manage key operations of a business. The technology in
big data is now widely used in various international and national companies to provide support to
key operations of the company. It is key role of a business to focus on dealing with major issues
and challenges related to big data in order to lead the competition. The big data analytic
challenges must be handled by information and technology and research and development
department of a business in order to gain expected results (Mittal, 2020). This is also one of the
key role of a business to focus on analysing the situation and take essential actions in order to
deal with the same. The major challenges in the field of big data technology are mentioned
below:
Integration of big data- It is one of the most crucial challenges in big data analytic
which states that integration of data is hard and necessary. Big data integration should be
done while taking into account application of systematic tools which done by data
analytic. It is essential for the business to focus on integration of big data in order to gain
competitive advantage (Nair, 2020). The integration of big data should be developed by a
researcher in order to increase then potential of business while managing customer
database.
Complex data- The data complexity is considered as one of the key issues in the field of
data management and analytic (Roh, Heo, and Whang, 2019). The complexity in data
creates a rigidity for the researcher that makes hard for data to be understood.
Arrangement of data is also essential for the researcher in order to develop a systematic
approach.

Key tools and techniques which are available to briefly assess and evaluate big data
The major techniques to analyse big data are explained below:
Machine learning- Artificial intelligence is the major part of machine learning which
helps a business entity to develop more precise operations. Many companies use big data
technology with the help and support of machine learning in order to develop
marketplace growth.
Statistics- The statistics and their development is also a major technique to analyse the
big data. 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.
Data mining- This is one of the most essential tools which is used by a business entity to
develop perfect approach in managing big data (Shams, and Solima, 2019). The data
mining is also used in order to develop precise synchronization and management of data.
The way big data technology can impact on functioning of an organisation
The big data technology is very much supportive to a business organisation in order to
develop a key approach at the marketplace. In the corporate world many domestic and global
companies use the application of big data to facilitate key operations. In order to increase the
competency edge of a business it is essential to support of big data technology. The key benefits
of Big data technology are mentioned below:
The big data technology is helpful in increasing huge set of data of major customers
which is essential for company development. In the era of stiff competition between
companies, it is essential for focus on big data technology in order to manage large
database of customers.
Focus on big data management in a well defined manner helps a business entity to
maintain privacy and other cybersecurity related issues (Zhao, Ren, and Meng, 2020).
The privacy of customers is one of the major priorities of a business which is handled by
the help of big data technology.
The development and expansion of an organisation is supported with the help and support
of big data technology. It is crucial for the business to evaluate key ways of business
development with functions performed through big data technology.
The major techniques to analyse big data are explained below:
Machine learning- Artificial intelligence is the major part of machine learning which
helps a business entity to develop more precise operations. Many companies use big data
technology with the help and support of machine learning in order to develop
marketplace growth.
Statistics- The statistics and their development is also a major technique to analyse the
big data. 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.
Data mining- This is one of the most essential tools which is used by a business entity to
develop perfect approach in managing big data (Shams, and Solima, 2019). The data
mining is also used in order to develop precise synchronization and management of data.
The way big data technology can impact on functioning of an organisation
The big data technology is very much supportive to a business organisation in order to
develop a key approach at the marketplace. In the corporate world many domestic and global
companies use the application of big data to facilitate key operations. In order to increase the
competency edge of a business it is essential to support of big data technology. The key benefits
of Big data technology are mentioned below:
The big data technology is helpful in increasing huge set of data of major customers
which is essential for company development. In the era of stiff competition between
companies, it is essential for focus on big data technology in order to manage large
database of customers.
Focus on big data management in a well defined manner helps a business entity to
maintain privacy and other cybersecurity related issues (Zhao, Ren, and Meng, 2020).
The privacy of customers is one of the major priorities of a business which is handled by
the help of big data technology.
The development and expansion of an organisation is supported with the help and support
of big data technology. It is crucial for the business to evaluate key ways of business
development with functions performed through big data technology.
⊘ This is a preview!⊘
Do you want full access?
Subscribe today to unlock all pages.

Trusted by 1+ million students worldwide

CONCLUSION
The mentioned analysis concludes that big data management is one of the most crucial
functions of a business entity which helps in increasing competitive strength. This project
concludes that it is necessary for a company to focus on dealing with issues and challenges of big
data in order to eliminate the chances of business failure. The privacy and cybersecurity related
concerns are essential to be analysed by a business in order to maintain safety and privacy of the
customers. This project concludes that in order to develop systematic approach in maintaining
big data, it is essential for a business to take precise support of IT professionals. This project also
concludes that key business operations related to big data should be handled with the help of
focused approach in order to formulate best business practices.
The mentioned analysis concludes that big data management is one of the most crucial
functions of a business entity which helps in increasing competitive strength. This project
concludes that it is necessary for a company to focus on dealing with issues and challenges of big
data in order to eliminate the chances of business failure. The privacy and cybersecurity related
concerns are essential to be analysed by a business in order to maintain safety and privacy of the
customers. This project concludes that in order to develop systematic approach in maintaining
big data, it is essential for a business to take precise support of IT professionals. This project also
concludes that key business operations related to big data should be handled with the help of
focused approach in order to formulate best business practices.
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REFERENCES
Books and Journals
Ahsan, U. and Bais, A., 2017, April. Distributed big data management in smart grid. In 2017
26th Wireless and Optical Communication Conference (WOCC) (pp. 1-6). IEEE.
Alharthi, A., Krotov, V. and Bowman, M., 2017. Addressing barriers to big data. Business
Horizons, 60(3), pp.285-292.
Karim, A., Siddiqa, A., and Imran, M., 2020. Big data management in participatory sensing:
Issues, trends and future directions. Future Generation Computer Systems, 107, pp.942-955.
Manogaran, G., Shakeel, P.M., and Muthu, B.A., 2020. FDM: Fuzzy-optimized data
management technique for improving big data analytics. IEEE Transactions on Fuzzy
Systems, 29(1), pp.177-185.
Mittal, P., 2020. Big data and analytics: a data management perspective in public
administration. International Journal of Big Data Management, 1(2), pp.152-165.
Nair, S.R., 2020. A review on ethical concerns in big data management. International Journal of
Big Data Management, 1(1), pp.8-25.
Roh, Y., Heo, G. and Whang, S.E., 2019. A survey on data collection for machine learning: a big
data-ai integration perspective. IEEE Transactions on Knowledge and Data Engineering, 33(4),
pp.1328-1347.
Shams, S.R. and Solima, L., 2019. Big data management: implications of dynamic capabilities
and data incubator. Management Decision.
Zhao, C., Ren, L., and Meng, Z., 2020. Master data management for manufacturing big data: a
method of evaluation for data network. World Wide Web, 23(2), pp.1407-1421.
Books and Journals
Ahsan, U. and Bais, A., 2017, April. Distributed big data management in smart grid. In 2017
26th Wireless and Optical Communication Conference (WOCC) (pp. 1-6). IEEE.
Alharthi, A., Krotov, V. and Bowman, M., 2017. Addressing barriers to big data. Business
Horizons, 60(3), pp.285-292.
Karim, A., Siddiqa, A., and Imran, M., 2020. Big data management in participatory sensing:
Issues, trends and future directions. Future Generation Computer Systems, 107, pp.942-955.
Manogaran, G., Shakeel, P.M., and Muthu, B.A., 2020. FDM: Fuzzy-optimized data
management technique for improving big data analytics. IEEE Transactions on Fuzzy
Systems, 29(1), pp.177-185.
Mittal, P., 2020. Big data and analytics: a data management perspective in public
administration. International Journal of Big Data Management, 1(2), pp.152-165.
Nair, S.R., 2020. A review on ethical concerns in big data management. International Journal of
Big Data Management, 1(1), pp.8-25.
Roh, Y., Heo, G. and Whang, S.E., 2019. A survey on data collection for machine learning: a big
data-ai integration perspective. IEEE Transactions on Knowledge and Data Engineering, 33(4),
pp.1328-1347.
Shams, S.R. and Solima, L., 2019. Big data management: implications of dynamic capabilities
and data incubator. Management Decision.
Zhao, C., Ren, L., and Meng, Z., 2020. Master data management for manufacturing big data: a
method of evaluation for data network. World Wide Web, 23(2), pp.1407-1421.
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