Big Data Analysis: Characteristics, Challenges, and Techniques

This study discusses the characteristics of big data, challenges faced by companies in managing and analyzing big data, and techniques that can be used to solve these problems. It also highlights the importance of big data technology in improving business performance and productivity. The subject is Information Systems and Big Data Analysis, and the course code is not mentioned. The content is relevant to students pursuing courses in data analysis, business intelligence, and information systems.

Information Systems and Big data
Analysis
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Table of Contents
INTRODUCTION...........................................................................................................................3
Big data and its characteristics....................................................................................................3
Challenges of big data analysis and techniques for analysing big data (500).............................4
Importance of big data technology in improving business performance.....................................5
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................7
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INTRODUCTION
Big data that is big in size and volume plays a vital role nowadays as it makes companies
able in talking better decision and performing all functions in an effective manner (Oussous and
et.al., 2018). This present study is going to discuss all main 5 characteristics of big data such as:
velocity, volume and others. It will further discuss some challenges that are associated with big
data analysis and management. It will also show some effective techniques that companies might
use for solving all problems that they face while managing and analysing big data. Along with
this, it will show ways in which companies can make use of big data in order to improve
business performance and productivity as well.
Big data and its characteristics
As with the name itself, it can be said that big data refers data that contains greater
variety or have complex data set. Such data is voluminous that cannot be managed with
traditional data processing software. In other words, it can be said that it refers a field that treats
ways of analysing and extracting information in order to make decision. There are number of
ways in which big data can help companies in improving their business performance. Some
characteristics of big data include:
Volume: It is one of the main characteristic of big data as it is related to an enormous
size (Sun, Strang and Li, 2018). It can be generated from number of sources such as: machines,
social media platforms, networks, human interaction and business processes. Facebook is one of
the great example that generates around a billion messages and around 350 million posts.
Variety: Big data can be generated in number of varieties as it may be structured,
unstructured and semi-structured. Such data were used to collect from sheets and databases but
now it may be collected in the form of audios, Emails, PDFs, photos and others. Structured data
is being stored in relational database management system and semi structured is being stored in
table format.
Veracity: It shows the extent of reliability of data. Veracity is one of the best process by
which data are being managed in an effective manner. It helps in improving business’
performance and development.
Value: It is one of the other main characteristic that makes businesses able in improving
their operations and making decision. It is not about data that businesses store as it is valuable
data that they store and make use.
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Velocity: This characteristic creates the speed by which data is being created in real time.
In other words, it can be said that it is related to rate of change, data set speed and activity bursts
(Hasanin and et.al., 2019).
On the basis of above characteristics, it can be said that by focusing on all these,
businesses can accomplish their goals by managing big data.
Challenges of big data analysis and techniques for analysing big data (500)
Managing big data is not an easy task as there are number of problems, associated with big
data. Employees face problems in managing big data because of some reasons such as:
Lack of proper understanding of massive data: Employees have few knowledge
regarding big data, was of managing, storing and processing. Only data professionals know what
is happening and how to manage big data and due to lack of knowledge and understanding, it
becomes difficult for employees to deal with big data and it may affect overall performance of
business.
For solving this problem, companies need to encourage their employees for participating in
big data workshops and seminars. Along with these, they can participate in military training
programs that companies should arrange for all workers who deal with big data. It can increase
knowledge and understanding of employees regarding big data management (Knüsel and et.al.,
2019).
Data growth issues: It is other main problem as the quantity of knowledge being stored in
data centres as well as database of companies is increasingly rapidly. Data sets grow at rapid rate
and with time, it becomes difficult to manage. Those data that is unstructured and comes from
text files, audio and videos, become very difficult to manage and understand.
This problem can also be solved out by making use of modern technologies such as
compression and deduplication. Compression is one of the best ways of decreasing size of files
or big data and by doing so, employees can understand big data in an effective manner. There are
number of techniques and tools that are also being use now days in order to solve all these
problems such as: Hadoop and noSQL.
Integration of data from a spread of sources: In corporations and big companies, big data
comes from number of sources such as: customer logs, social media pages, E-mails and reports
that are created by employees. Employees find difficulties in combining data, gathered from all
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these sources. Data integration is known as crucial for reporting, analysis and business
intelligence (Wang and et.al., 2018).
Securing data: Along with management of big data, it is also challenging for businesses to
securely save them. Companies find difficulties in understanding and string data so they push
data security for later stages. It is not a sensible move as it can affect image of companies to the
great extent. So, it is important for companies to focus on this factor.
For solving this problem, companies can recruit cyber security professionals as they can
help companies against breaches of data. There are other ways and technologies by which also
companies can solve this problem such as: data encryption data segregation identity.
For solving this problem, companies need to focus on solving data integration problem by
purchasing proper tools proper tools such as: centerprise data integration, ArcESB and others.
All these tools can help out corporations in solving all these problems related to big data
management.
Importance of big data technology in improving business performance
There are number of advantages that companies can take by making use of big data
technology such as: better informed decision, improvement of supply chain, cost saving and
improved organisational performance. In addition, it can also be said that big data technology
help companies to the great extent as it generates valuable insights and companies make use of
analysed big data in order to refine marketing campaigns and techniques. Companies use it in
machine learning projects in order to train machines and for predicting modelling (Dubey and
et.al., 2019). Some techniques that can be used for managing big data include: MongoDB,
Apache Cassandra, Qlik view, Tableau and others. Companies like Google, Twitter and
Facebook also make use of these technologies and manage big data,. It helps them out in making
better decision and improving performance.
Big data technology is an open source NoSQL that is beneficial for storing and managing
data. Companies find easier in identifying new opportunities and by taking advantages of new
opportunities, they take competitive advantages. It in turns lead smarter business moves and
efficient operations. Some other advantages of big data technologies include:
Improving productivity: when employees perform their functions with anslysed big data,
then they are more likely to improve their performance by decreasing errors and mistakes. It
boosts their confidence and they help company in increasing customers retention rate that is vital
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for improved image of company. Companies like face book and Google are successful examples
of this that has made use of big data management technologies and now they are known as the
market leader.
Fraud detection: It is already known that managing big data is not an easy task and
security data breaches is one of the main problem that businesses face. But by making use of big
data management technologies, companies can protect themselves against fraud and security
challenges and by doing so, they can improve their image in the market. It can also help them out
in taking advantages of external opportunities like attracting customers and increasing market
shares (Pappas and et.al., 2018)
CONCLUSION
It has been summarised from the above study that big data plays a vital role as it can make
companies able in making decision as well as improving overall performance of business. It has
discussed some problems that corporations or employees face while managing and storing bid
data due to lack of knowledge and others. It has further discussed some strategies as well as
software that can be used by companies for solving all these problems. This study has shown
some ways in which companies can improve its overall business operations by making use of big
data and managing data in an effective manner.
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REFERENCES
Books and journals
Oussous, A. and et.al., 2018. Big Data technologies: A survey. Journal of King Saud University-
Computer and Information Sciences. 30(4). pp.431-448.
Hasanin, T. and et.al., 2019. Examining characteristics of predictive models with imbalanced big
data. Journal of Big Data, 6(1), pp.1-21.
Knüsel, B. and et.al., 2019. Applying big data beyond small problems in climate research. Nature
Climate Change, 9(3), pp.196-202.
Wang, H. and et.al., 2018. A hybrid multi-objective firefly algorithm for big data
optimization. Applied Soft Computin. 69. pp.806-815.
Dubey, R. and et.al., 2019. Big data and predictive analytics and manufacturing performance:
integrating institutional theory, resource‐based view and big data culture. British Journal
of Management. 30(2). pp.341-361.
Pappas, I.O. and et.al., 2018. Big data and business analytics ecosystems: paving the way
towards digital transformation and sustainable societies.
Sun, Z., Strang, K. and Li, R., 2018, October. Big data with ten big characteristics.
In Proceedings of the 2nd International Conference on Big Data Research (pp. 56-61).
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