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

This report discusses the characteristics, challenges, and techniques of big data analytics. It explores the five Vs of big data and the available techniques for analysis. The report also highlights the impact of big data on decision-making, consumer understanding, and revenue generation.

INFORMATION
SYSTEMS AND BIG
DATA ANLYSIS

Table of Contents
INTRODUCTION ...............................................................................................................................3
TASK ...................................................................................................................................................3
What big data is and the characteristics of big data? ...........................................................................3
The challenges of big data analytics; and the techniques that are currently available to analysis
big data ............................................................................................................................................3
How Big Data technology could support business, please use examples wherever necessary. ......3
CONCLUSION ...................................................................................................................................3
REFERENCES ....................................................................................................................................4

INTRODUCTION
Big data is basically a set of data which is to big and complex which data have many rows,
columns, and attributes, and increases day by day. It is difficult to proceed with any traditional data
processing tools and soft-wares can process this in a appropriate way. Big data aids the organisation
in boosting up the performance as well the productivity. Big data is generally used to predict the
analytics, analytics of user behaviour and many other data analytics methods (Hariri, Fredericks,
and Bowers, 2019). The respective report is based on big data analytics. What does it means and
what are its characteristics is discussed below. Further, the report is based on the challenges of the
big data analytics and what are techniques available fr the analysis of big data. Lastly the reports
includes that how the technology of big data is supporting businesses with a proper example
(Hancock, and Khoshgoftaar, 2020.).
TASK
What big data is and the characteristics of big data?
Big data refers to the complex, organised and unorganized data. These data sets are so large
in size which traditional data processing software cannot process them. This complex data is used to
identify the business problems and their solutions. This valuable data is collected by the clients,
suppliers, sales, purchases, employee's and company's history. Different sources which provides
information regarding business aids in not only in enhancing the organisational structure but it also
helps in the effective and efficient decision making process. For instance, big data is used in social
media, new york stock exchange and many more. There are five Vs of big data means greater
variety, increasing volumes, more velocity, veracity and value. Discussed below (Deepa, and et. Al,
2022.).
 Volume – this is the first Vs of big data , this basically refers to the quantity of data exist.
This the base of data as the data is collected is of the initial size and amount. The amount of
data is very complex in nature and stored in petabytes and exabytes. This data is basically
used in advanced processing technologies like Instagram, twitter and many more.
 Variety – the next V is variety, which refers to the variety of data types. There are many
internal as well as the external sources of information through which the data is collected.
The collected data can be organised, unorganized, or semi-organised and comes in various
files and formats. Earlier there was traditional data like phone numbers, addresses and many
more, but nowadays data is in the format of audio, video, photos and many more.
 Velocity - the third V of big data is velocity, which refers how fast the data is created and

how speedily it moves. This is one of the crucial part for companies who wants their data to
flown rapidly. As there is complex and continue flow of data, the data should be analysed
quickly and in real time.
 Value – the second last V is value, which refers to the value of big data. It directly linked
with what organisations can do with that stored data. The ability to pull value from big data
is needed, a the value keeps increasing by the insights obtained from them. Companies can
use tools of big data to collect and analyse the data and derived value will be unique. The
data will be authentic, reliable, valuable and evaluated.
 veracity – the last V is veracity, this basically refers to the quality, authenticity and the
accuracy of the data. The collected data might be inaccurate, incomplete, or with missing
pieces. There is no use of big data, if the data is not appropriate and accurate. That is why it
is crucial to check the authenticity of the data (Wang, and et. Al, 2020).
The challenges of big data analytics; and the techniques that are currently available to
analysis big data
The big data plays a very important role in the organisation nowadays, as it not only aids
the organisation in the controlling the risk factors but also helps them in making the quick and
effective decision for the business. Apart from this, this enables the accountability in the firm,
improves financial health which helps the company as well the employees in analysing and
predicting their overall performance. The challenges of big data are discussed below: -
 lack of understanding of massive data – due to the inadequate understanding and
knowledge, big data can not be beneficial for the company. The workers will not be able to
interpret about data, its process, importances and storage. They might not be having
appropriate knowledge regarding that. To overcome this, there should be regular seminars or
workshops for the employees in order to educate them.
 Data growth issues – one of the important challenge of big data is to collect and store the
complex data in a very systematic manner. The data is basically gets stored in the data centre
as well as in the organisation's database. day by day the data keeps on increasing and it
becomes hard to manage. The company should use compression and tiering to overcome this
challenge (Zicari, 2014.).
The techniques of big data is very crucial for the organisation as it helps them in analysing, storing,
and understanding the data. The decisions can be quick and efficient by the help of these
techniques and the risk factors can be decreased. Some of the techniques which are available to big
data analysis is discussed below: -
 A/B test – by the use of this technology, companies can focus towards on comparing

different variety of test groups. To recognise the appropriate treatment or modification, the
controlled group of data boost up the target variables. Though this technique, organisation
can operate in a effective manner.
 Data integration and data fusion - these both are basically designed to organise the data
with is collected through different sources. This technique gives a successful insights for the
effective and appropriate data gathered by an individual (Gil, and Song, 2016).
How Big Data technology could support business, please use examples wherever necessary.
To understand the consumers behaviours and preferences and to maintain a fixed customer
base big data technologies are necessary for all the companies. the impacts of big data in
supporting the businesses are discussed below: -
 better decisions for organisation – big data aids the business to make quick and better
decisions for the business on the basis of authentic data, not on the assumptions of data.
That's known as the data democratization because it provides helps in researching the data
by the user. For instance, in walmart the access is provided to people is in very disciplined
and controlled way (Vlahogianni, 2015.).
 Understanding consumer – through big data analytic, employees can easily understand
the needs and wants of consumers and their preferences and can satisfy them with their
products and services. For instance, big data is applied by Disney, in Disney they started
giving wristbands as the entry key for the theme park to understand the behaviour of
customers.
 Enhancing the business operations – nowadays the companies are becoming more
automatic day by day and that is happening because of the use of big data in the business
organisation. For instance, to maintain the interaction wit the organisation workers use chat
bots.
 Generate income – big data help and support the business organisations in making their
operations much more easier, handling the processes of decision making and also aid the
company in increasing their revenues as well as the income of the employees. For instance,
big data is used by American express to analyse their transactions ads well as their
customers and keep the strong relations with consumers.
 Providing genuine products and services - with the help of big data, company can easily
and effectively figure out the needs, wants and the preferences of the consumer and helps
in designing the product automatically. For instance, to offer the best services to the
customers the royal bank of Scotland uses this which results in saving the money and time

as well (Li, Y. and Chen, 2014).
CONCLUSION
The above respective report concludes that the big data is collection of complex data which
is not able to processed by any traditional data processing tool or software. This can enhance the
performances of the organisation. There are basically five characteristic of the big data which is
volume, velocity, value, variety and veracity. There are also some challenges of big data which are
lack of understanding of massive data, data growth issues and many more and techniques currently
available to analyse big data is A/B test, Data fusion and data integration. There big data technology
supports businesses in many ways like better decisions for organisation, Understanding consumer,
Enhancing the business operations, Generate income, and Providing genuine products and services.

POSTER

REFERENCES
Books and journal
Hancock, and Khoshgoftaar, 2020. CatBoost for big data: an interdisciplinary review. Journal of big
data, 7(1), pp.1-45.
Hariri, Fredericks, and Bowers, 2019. Uncertainty in big data analytics: survey, opportunities, and
challenges. Journal of Big Data, 6(1), pp.1-16.
Deepa, and et. Al, 2022. A survey on blockchain for big data: approaches, opportunities, and future
directions. Future Generation Computer Systems.
Wang, and et. Al, 2020. Big data service architecture: a survey. Journal of Internet
Technology, 21(2), pp.393-405.
Zicari, 2014. Big data: Challenges and opportunities. Big data computing, 564, p.103.
Gil, and Song, 2016. Modeling and management of big data: challenges and opportunities. Future
Generation Computer Systems, 63, pp.96-99.
Vlahogianni, 2015. Computational intelligence and optimization for transportation big data:
challenges and opportunities. In Engineering and Applied Sciences Optimization (pp. 107-
128). Springer, Cham.
Li, Y. and Chen, 2014. Big biological data: challenges and opportunities. Genomics, proteomics &
bioinformatics, 12(5), p.187.