Big Data Analytics: Characteristics, Challenges, Techniques and Business Support

This report discusses the characteristics, challenges, techniques and ways in which big data analytics can support businesses. It covers topics such as volume, variety, velocity, lack of professional knowledge, confusion relating to use of techniques, data mining, machine learning, statistics, decision making, predicting future demand and more.

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TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
Big data and its characteristics....................................................................................................3
Challenges of big data analytics..................................................................................................4
Techniques available for analysing big data...............................................................................5
Ways in which big data analytics support business....................................................................5
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................8

INTRODUCTION
The big data is being defined as the process of examining the data which is large in
numbers and identify the hidden patterns. This is essential for the businesses to analyse and
evaluate big data in order to identify the trends and working patterns. It is crucial for the business
as it will assist the company in taking better and effective decision for the growth and
development of business. the present report will outline the characteristic of big data. Along with
this analysis of the challenges relating to big data analytics will also be evaluated. Moreover, the
report will also outline the various techniques which is available for analysis of big data. In the
end, the various ways will be analysed through which big data analytics can support the business.
Big data and its characteristics
Big data is being referred to as the massive amount of data which need to be analysed and
evaluated in order to take some decision. For the business to grow it is very crucial that the
effective analysis of the data relating to different problems of business (Hariri, Fredericks and
Bowers, 2019). there are various techniques through which company can undertake the use of
big data in order to take various decision of business and provide a growing direction. The major
characteristic of big data involves the following-
 Volume- this is the key characteristic of the big data as the name suggest the data is in
large volume. This is particularly because of the reason that when the business is being
running then in that situation the company will be involved in use of different large set of
data. Thus, this will be affecting the working and decision making pattern of the
company. the reason underlying this fact is that when the company will be using large
volume of data then this will provide a better and effective analysis and presentation of
actual picture of company.
 Variety- In addition to this, another key characteristic of big data is the large variety. The
data being provided involves a different type of variety of data. Hence, this provides for a
better and effective base for the evaluation of the data. The reason underlying this fact is
that when the company will be having variety then they can confirm the data and its
authenticity by cross checking the variety of data.
 Velocity- Along with this another key characteristic of the big data is the velocity of data.
This velocity of data is being defined as how quickly the data is coming and is being

recorded and stored for the future use. This is essential for the big data to be utilised in
proper and effective manner (Ghani and et.al., 2019). The reason underlying this fact is
that when the data is recorded on time and stored at correct place then this will be
accessible by the company at any point of time. Thus, at time of taking any decision the
use of big data will be assistive in case all these three characteristic are being fulfilled.
Challenges of big data analytics
With the various characteristic of big data there are also some of the challenges which the
company faces while operating with big data. The data is large in number and because of this the
company can face some problems in managing and using the big data. The list of various
challenges which the companies can face due to big data analytics are as follows-
 Lack of professional knowledge- The most important challenge which can impact the use
of big data analytics is the lack of professional knowledge. This is particularly because of
the reason that when the big data is being used then it is not necessary that the person is
having proper knowledge relating to how to use the data. Hence, sometimes this can
cause problem and issue in analysing and using big data.
 Confusion relating to use of technique- Along with this another key challenge which can
be faced due to big data is that there can be some confusion being created by the user that
which kind of tool need to be applied for the application of the big data. This is a
challenge because of the reason that there are different types of tools and techniques
available for the big data analytics. Also, the person might be confused as which
technique need to be applied at what time.
 Integration of data from different sources- there are many different sources through
which the company can gather and collect data. It is not necessary that the company
know which is the reliable source (Big data analysis techniques, 2021). Also, it may be
possible that different sources provide some different information and it may not be
possible for the company to decide which information is correct and which is not.
 Need of synchronization of data- when the work is being done with help of big data then
there is high requirement of synchronizing the data. This is necessary because of the
reason that when the effective big synchronization is not there then this will be affecting
the working in effective manner as there will be very mismanagement of the data.

Techniques available for analysing big data
There are many different techniques which can be used by the company in order to
analyse big data (Zhu and et.al., 2018). These techniques make it easier for the companies to
work in better and effective manner. The various techniques available for the analysis of big data
are as follows-
 Data mining- this is a technique which involves analysing data mining extract patterns
from large set of data. In simpler terms, the company draws some of the patterns and
trends from whole big set of data. This is essential for the reason that these trends will
acknowledge the people that how they can manage their own data.
 Machine learning- this is another technique through which big data can be managed in
proper and effective manner. This a field of artificial intelligence and this can also be
used by the company in order to analyse the big data. This is particularly because of the
reason that when this method works with computer algorithms and as a result of this, the
data is being utilised and analysed in proper and effective manner.
 Statistics- this is another technique of analysing the big data and drawing some
conclusion from the data. Statistics involves collection, organizing and analysing the data
in such a manner that some meaningful inferences can be drawn from it. Hence, as a
result of this, the big data will be analysed in proper and effective manner.
Ways in which big data analytics support business
There are many different ways in which big data analytics can be used by company and
support the business and its operations. This is very important for the business to analyse and
interpret the big data so that business can plan all its operations in proper and effective manner.
There are many reason for which big data analytics supports the business and its activities which
are as follows-
 These big data analytics is assistive for businesses to take decision for the betterment of
the business (Saggi and Jain, 2018). This is particularly because of the reason that when
the big data is used then it provides better and effective picture of the company. thus, on
the basis of the effective analysis of data, the company can take proper decision.
 Along with this, the big data analytics is being used by the companies for analysing the
consumer trend and preferences. This is particularly because of the reason that when the
big data is being stored then company can also store data relating to consumers and their

preferences. Hence, it is necessary for the company to apply different data analysis
techniques and try to evaluate the latest trends with the data present.
 Also, this big data analysis used by the company is also assistive to business in predicting
the future demand of the company (Mikalef and et.al., 2019). The reason underlying this
fact is that with help of the past data, the company can try to predict the future demand as
well. hence, as a result of this the company can direct the operations in order to meet the
forecasted demand in proper and effective manner.
CONCLUSION
The above report concluded that big data analytics is very important for business to get
successful. The reason behind this fact is that it will assist the company in analysing the data and
take business decision for the betterment of working. These big data analytics involves various
characteristics like velocity, volume and others. Along with this, it was also evaluated that there
are some challenges being faced like lack of professional knowledge, confusion relating to use of
techniques of big data and others. Further it was analysed that there are various techniques
assistive for analysing big data. This involved techniques like data mining, statistics and others.
In the end, it was evaluated that big data is assistive for business like in decision making,
predicting future demand and others.
Poster

REFERENCES
Books and Journals
Hariri, R. H., Fredericks, E. M. and Bowers, K.M., 2019. Uncertainty in big data analytics:
survey, opportunities, and challenges. Journal of Big Data. 6(1). pp.1-16.
Ghani, N. A. and et.al., 2019. Social media big data analytics: A survey. Computers in Human
Behavior. 101. pp.417-428.
Zhu, L. and et.al., 2018. Big data analytics in intelligent transportation systems: A survey. IEEE
Transactions on Intelligent Transportation Systems. 20(1). pp.383-398.
Saggi, M. K. and Jain, S., 2018. A survey towards an integration of big data analytics to big
insights for value-creation. Information Processing & Management. 54(5). pp.758-790.
Mikalef, P. and et.al., 2019. Big data analytics and firm performance: Findings from a mixed-
method approach. Journal of Business Research. 98. pp.261-276.
Online
Big data analysis techniques. 2021. [Online]. Available through: <
https://www.getsmarter.com/blog/career-advice/big-data-analysis-techniques/>