Information Systems: Big Data Analytics, Challenges & Business Use

This report provides a comprehensive overview of big data, defining it as a combination of structured and unstructured data used for optimized decision-making. It details the key characteristics of big data, including volume, velocity, variety, veracity, and value, explaining how these aspects influence data management and analysis. The report further explores the challenges associated with big data analytics, such as a lack of skilled professionals and difficulties in handling unstructured data, and discusses techniques like data mining, machine learning, and natural language processing used to overcome these challenges. Furthermore, it highlights how big data technology supports business by improving operational efficiency, enhancing customer satisfaction, ensuring data security, boosting sales, and managing online reputation, emphasizing its role in data-driven decision-making for both public and private sectors. Desklib provides access to this and other solved assignments.

Information Systems
and Big Data Analysis

Table of Contents
INTRODUCTION ..........................................................................................................................2
MAIN BODY...................................................................................................................................2
1.Explain big data and the characteristics of big data ................................................................2
2.The challenges of big data analytics; and the techniques that are currently available to
analysis big data..........................................................................................................................3
3.How Big Data technology could support business, please use examples wherever necessary4
CONCLUSION................................................................................................................................4
REFERENCES................................................................................................................................6
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INTRODUCTION
Big data is said to be a combination of structured and unstructured data which is collected
by the company in order to take best decisions for the purpose of better optimization of large
data. The report is going to demonstrate the various features of big data such as velocity, volume,
variety, validity, volatility, visualization and veracity (Hopkins and Hawking, 2018). The report
further explain the challenges of big data analytics and the various techniques which are
currently available to analysis big data. Nowadays, big data supports the business with the
development of apps and it also helps in identifying the latest trends of the market in order to
compete with the competitors (Sedkaoui, 2018). It also helps in scanning the market trends in
order to reduce the risks of the market for customers, suppliers and other stakeholders.
Moreover, big data allows to keep the data safe and it has also transformed the various segments
by real-time tracking.
MAIN BODY
1.Explain big data and the characteristics of big data
Big data
Big data manages the complex set of data as the traditional methods can not manage the massive
data and it is the combination of structured and unstructured data which is collected by the
company in order to take best decisions for the purpose of better optimization of large data. Big
data technology is useful for both the public and private sector of the market. Under this, the data
is sourced from various sources such as ledgers, search history, employee records, customer
profile information and many others.
Characteristics of big data
Primary characteristics of big data are explained below- Volume-Companies use and collect the data from various sources for example videos,
images, social media, images and many others (Dey and et.al., 2018). Earlier, storing data
used to be an issue but nowadays, it has become more affordable because of the
availability of the resources. Velocity- big data assists with the speed of the data that flows from different sources such
as application logs, processes, networks, mobile devices, sensors and many others.
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 Variety-It refers to data which is in variety for example structured, semi-structured or
unstructured data where the data can be in the form of emails, videos, photos, PDFs and
audios. Veracity- It is the fourth V which is related to the quality and accuracy of the data
whereas the data can create certain problems and will be difficult to use. Veracity helps to
define the quality with the insights collected from data.
 Value-Companies can use big data in order to gather the data which is related to the
organisation and it is one of the important V of all the 5Vs.
2.The challenges of big data analytics; and the techniques that are currently available to
analysis big data
The challenges of big data analytics
Big data has various ways to handle the large data and it includes various ways to store, analyse
the data there are some major challenges that take place while dealing with the big information.
Various challenges are explained below-
 The main challenge is that the companies have less knowledge of the big data initiative
that can create issue in understanding and also some employees may not have
knowledge about the data, its storage and the various sources. Only professionals can
understand about the bigger picture.
 In order to operate the tools of the big data, the companies require data professionals
such as data analysts or data engineers. The company may face serious issues due to less
data professionals in the company. As the companies choose new techniques to deal with
the large data for example tiering, compression, deduplication and many others. When the data is unstructured then it will be difficult to store the information in
database form or the spreadsheet table. Moreover, it become difficult to deal with the
various challenges in order to research and analyse the data.
The techniques that are currently available to analyse big data Companies can invest more in the hiring the skilled professionals and in addition to that
proper training can also be provided to make the professionals more capable so that they
can manage the data easily.
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 Data mining is one of the tool that is used to manage the big data from various sources
that further helps in finding the patterns of the large set of the data. It also enhances the
organisational decision making power of the company.
 Another technique is known as Machine learning that also improves the overall
experience with the help of data. As it based on the sample data and it enables the
computer to tackle various tasks by different people. Another technique is known as NLP (Natural language processing) that helps to
communicate with the humans as per their own language and scales such as it helps to
read text or hear speech. As NLP supports the efforts in multiple ways for example it
helps in dealing with the global problems and providing help to the people who are not
even trained in the data processing. A/B testing is said to be a technique that is used to analyse the big data which helps in
improving the engagement of the user with improved version of content.
 Data fusion and integration supports in combining the data from various sources in
order to be more consistent and accurate while making use of information.
3.How Big Data technology could support business, please use examples wherever
necessary
Role of big data in business
Big data technology is useful for both the public and private sector of the market and it plays an
important role in combining the tools which are related to managing the large amount of data and
it also create new growth opportunities for the company which are explained below- Improve efficiency- Big data is a tool that improves the efficiency of the operations led
by the company and such analytics also helps in identifying the main trends of the market
by competing with the competitors of the market (Dey and et.al., 2019). Make the customers satisfied- Customers are main in any business and in which big data
allows to observe the behaviour of the customers with the help of online preferences. Keep the data safe- Big data supports in keeping the data safe as it has more
professionals that helps in managing the data to reduce the level of risk and safeguard
the sensitive data.
 Elevate sales- Big data allows to gather the large data of the customers and get the digital
footprints about the buying behaviour of the customers in order to provide the scope to
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design the products as per their choice. When the quality products are offered to the
customers then they will be keep coming back to the same company.
 Online reputation-Now a days, businesses are shifting online that is why it has become
difficult for the companies to track and monitor the data in order to improve the online
presence of the company. It can be said that big data is said to be a powerful tool of the
business as it opens the opportunities for the company (Choi, Wallace and Wang, 2018).
CONCLUSION
It can be concluded from the above report that big data is useful in identifying the weak areas so
that the best ways can be found for issues in order to enhance the overall operations. The report
highlighted the features of big data and the various challenges of the big data analysis such as
lack of professionals, lack of proper understanding of massive data, growth issues and many
others. The report also explained the role of big data technology that helps in supporting the
business as it helps in making the data driven decision making of the company.
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REFERENCES
Books and Journal
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.
Dey, N., Das, H., Naik, B. and Behera, H.S. eds., 2019. Big data analytics for intelligent
healthcare management. Academic Press.
Dey, N., Hassanien, A.E., Bhatt, C., Ashour, A. and Satapathy, S.C. eds., 2018. Internet of things
and big data analytics toward next-generation intelligence (Vol. 35). Berlin:: Springer.
Hopkins, J. and Hawking, P., 2018. Big Data Analytics and IoT in logistics: a case study. The
International Journal of Logistics Management.
Sedkaoui, S., 2018. Data analytics and big data. John Wiley & Sons.
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