INFT6201-Big Data in digital Entertainment

Running head: BIG DATA IN DIGITAL ENTERTAINMENT
BIG DATA IN DIGITAL ENTERTAINMENT
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BIG DATA IN DIGITAL ENTERTAINMENT1
Introduction
This report aims to discuss the topic Big data in digital entertainment. A brief
discussion of the industry of entertainment before the implementation of big data is provided
in this report. A detailed discussion of the application of big data in the sector of
entertainment and media is provided in this report. A comprehensive discussion of the
analysis of the needs of industries in the sector of media and entertainment is provided in this
report. A brief discussion of the importance of big data analytics is provided in this report. A
discussion of the techniques of predictive analytics is provided in this report. The major
issues of big data is provided in this report. Lastly, this report concludes with an appropriate
conclusion for this report.
The term big data refers to the datasets that are significantly large or complicated for
the conventional software application of data-processing for adequately deal with (Swan,
2013). The data with several cases provide greater power of statistics, while the data with
higher complexity can lead to the higher discovery rate that is false. The challenges of big
data includes the data capturing, storage of data, analysis of data, search , transfer, sharing,
visualisation, querying, privacy of information and updating (Provost & Fawcett, 2013). It
also refers to the utilisation of predictive analytics, analytics of user behaviour, or several
other advanced methods of data analytics that can extract important value from data1, and
produce data to a specific size of data set.

BIG DATA IN DIGITAL ENTERTAINMENT2
Discussion
The publishers, organisations of news, broadcasters and the companies of gaming in
the entertainment and media industry are now facing new models of business for the methods
by which the creation, marketing, and the distribution of the content is executed (John
Walker, 2014). This is happening because of the present search and access content of
consumers from anywhere, at any time and on any device. This leads to the increased
pressure for executing innovative digital production and the advertising that is done multi-
channel and strategies of distribution that relies on a particular understanding of the
preferences and the behaviours of the consumption of media of the consumers (Wu et al.,
2014). And, due to the interest shift of the consumers from the analog to the media that is
digital, there are substantial opportunities for monetising the content and for identifying
innovative services and products.
Industry of entertainment before Big data
In the age of digital media, there are several connected devices for the automation
tasks (Lazer et al., 2014). These devices produce a huge amount of information that can
provide huge information about the customers. The information varies in formats and
frequently altering the result in the formation of the big data. When the organisations of
media and entertainment do not leverage this kind of technology, they can miss on a number
of opportunities (Raghupathi & Raghupathi, 2014). One of the primary losses in the losing
out on the actionable insights. Commonly, the conventional entertainment authorities
focusses on the decision taking that are based on the patterns that are long-established for the
decisions that are not working in their respective favour (Murdoch & Detsky, 2013). While
undertaking such decisions that are based on the traditional model can usually land the
organisations with huge debts or it can also suffer enormous losses when there is a failure in
the strategy.
Application of big data for the entertainment and media sector
With the increase of the consumers of digital media from thousands to millions, the
industry of media and entertainment are in a unique position of leveraging the assets of big
data for increasing the profitable engagement of customer (Gandomi & Haider, 2015). The
usage of big data in the entertainment industry helps in obtaining the insights of the trends of

BIG DATA IN DIGITAL ENTERTAINMENT3
customers, the schedules of shows and the trends of advertisements. The utilisation of smart
devices is rising in the present times. According to a research, 29% of the people all over the
world spend approximately 4-6 hours on their smartphones daily (Hashem et al., 2015). The
viewing of entertainment has been changed with the increase of smartphones users. As a
broad platform of entertainment is provided by the smartphones, the companies that are
dealing with the media and entertainment are also turning towards the technological
platforms, which can help them in experiencing the transformation. As enormous amount of
information are generated by the smart devices, when all the big data is analysed, it can assist
in the obtaining of actionable insights about the information that can assist them in the
addition of strength to the processes of decision-making (Chen, Mao & Liu, 2014). The
aspect of big data in the industry of entertainment can be a technology that can assist the
houses of media in experiencing the analytics innovation. Some of the examples how
entertainment and media companies can gain benefits from the applications of big data.
Several organisations tend to schedule the shows at the times and the days according
to the customers for preventing the losses of TRP and the revenue loss. With the analytics of
big data, the CIOs and the CTOs of the companies have the information of the slots of time
when their shows can generate the highest TRPs (Chen & Zhang, 2014). With the help of the
available platforms of social media, finding the likes and the dislikes of the customers poses a
challenge for the houses of media, as these companies have the ability of analysing the
collected data from these sources for knowing the preferences of the customers. Actionable
insights can help the companies in the process of planning the shows in a manner, which can
attract the attention of the customers.
With the help of the analytics of big data, the companies can also strategize the
methods of tweaking the subscription offers for generating increased profits (Sagiroglu &
Sinanc, 2013). The CTOs and CIOs of the house of media and entertainment should also
study the success of other companies for generating plans for development. Apart from the
learning processes, the companies can also focus on the training of the employees for
working with the software that can assist them in the insight obtaining from the information
in their possession.
Predicting the preferences of the customers
The scope of the collected big data by the industry of media and entertainment and for
potentially mining it for understanding the preferences of content, shows, music and the