Big Data Privacy

This presentation explores the importance of big data privacy in social media, discussing its characteristics, advantages, and challenges. It also provides recommendations for dealing with big data privacy issues in the future. The presentation highlights the role of machine learning and data scientists in addressing these issues and emphasizes the need for businesses to invest in IT infrastructure for data security. It concludes by discussing the benefits of big data technologies and privacy in social media, such as cost and time effectiveness, new product development, and market understanding.

Big Data Privacy
Name of the Student
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Introduction
 Big data is stated as a significant field, which majorly
treats various methodologies to analyse, systematic
information extraction (Constantiou & Kallinikos, 2015).
 Big data helps to deal with numerous data sets that are
much complex and larger in size.
 The three characteristics of big data are 3Vs, which are
volume, variety and velocity of data.
 Big data in social media helps to maintain data security
and privacy by elimination of complexities (Chen, Chiang
& Storey, 2012).

Description of Big Data
characteristics
 The first V is the huge or extremely volume of data,
which is measured on the size of the data within an
organization.
 The second V refers to broader or wider variety of
data types to understand the different variety and
deal with data complexity.
 The third V refers to the velocity at which the data
sets are being processed by the respective user.

Understanding Big Data Privacy
 Big data, being a major technology to properly use user
behaviour analytics, any advanced data analytics method and
predictive analytics.
 New correlations are being searched to spot major business
trends, disease prevention, combating of crime and several
others.
 The governments, advertisements and executives of
businesses can deal with difficulties with large data sets.

Big Data Privacy Contd..
 The data sets can grow rapidly since they are
gathered by cheap information sensing Internet of
things such as RFID, wireless sensor networks,
mobile devices, remote sensors, cameras and
software log.
 Big data privacy is considered for voluminous data
that are being collected from various sources such
as business transaction systems, social networks,
real time data sensors, mobile applications and
customer databases.

Big Data Privacy Contd..
 As data are collected in raw form with data mining
tools and data preparation software, there is always a
high chance that data might lose its confidentiality
and hence losing privacy.
 Moreover, since big data is mainly concerned about
large data sets, it becomes quite easier for hackers to
hack these data sets.
 Bid data even reveals any type of hidden pattern for
identification of secret correlation, privacy issues are
common.

Importance of Big Data Privacy in
Social Media
 Sagiroglu and Sinanc (2013) stated that, privacy of big data is
one of the most important feature, which is needed to be
considered and analysed in any business for ensuring data
safety.
 Breaching of users’ data could be stopped if big data is kept
safe and secured, which is extremely common in social media.
 Personal data is being collected in social media website to add
value to data process (Lu et al., 2014). It can cause data theft
in processing and storage phases.

Importance of Big Data Privacy
Contd..
 Kaisler et al. (2013) have stated in their journal
about PPDP or privacy preserving data mechanism
to eradicate issues related to data security in social
media.
 Access to the confidential data is strictly restricted
and hence data techniques are utilized.
 Encryption based techniques are effective in this
case and issues related to data theft and processing
in social media are avoided (Zhang, 2018).

Importance of Big Data Privacy
Contd.
 The two techniques of big data hat are required for
data security are social network analysis and machine
learning.
 An important application tool of big data is Hadoop
that can be used in social media website to maintain
effectiveness.
 Issues related to privacy are required to be eliminated
with the help of big data technology and thus data
loss of users could be removed in an efficient manner
(Victor, Lopez & Abawajy, 2016).

Advantages of Big Data
Technologies and Privacy in Social
Media
There are some important and significant advantages of big
data technologies and privacy in social media and these are
as follows:
 Cost Effectiveness: Big data technology is extremely cost
effective and hence any business can afford this technology
to ensure that the data is safe and secured with few tools
like Hadoop and Cloud based analytics (Eckhoff & Sommer,
2014).
 Time Effectiveness: The next advantage of this
technology is that it is extremely time effective and does
not incur huge time to recognize data (Yu, 2016).

Advantages of Big Data
Technologies and Privacy Contd..
 Helps to Develop New Product: Big data is even quite helpful
for better development of a new product. Thus, innovation and
creativity are enhanced by this technology (Katal, Wazid &
Goudar, 2013). Twitter and Facebook platforms can provide new
updates or news related to big data.
 Understanding Market Conditions: By analysing market, big
data can understand market conditions easily (Kshetri, 2014).
 Controlling Online Reputation: Big data helps to control
online reputation with help of several tools.

Advantages Contd..
 Easy Data Management: Big data even helps to
manage complex data sets in an effective manner by
involving few calculated metrics (Xu et al., 2014).
PPDM technique is being used for this purpose.
 Real time Forecasting: Real time forecasting and
data monitoring is possible with big data (Kallinikos &
Constantiou, 2015).
 Effective Decision Making: The next advantage of
big data technologies is that it helps in improving
decision quality.

Issues Faced for Big Data Privacy in
Social Media
In spite of having advantages, there are few issues
that are extremely common for the big data privacy in
social media and these issues are as follows:
 Major Concern about Privacy and Security: This
is the first and the foremost issue of big data privacy.
The various emerging applications of big data are
concerned about privacy and security (Sharma,
Mithas & Kankanhalli, 2014). An example of such
issue was faced in Facebook, where customers’ data
were breached and hence they faced major issues.

Issues Faced for Big Data Privacy
Contd..
 Major Requirements and Challenges for
Technology: This is the second major disadvantage
of big data privacy. To ensure accurate and proper
data, technology involved to deal with the issues
should be proper and error free. Since a business
requires processing capabilities and technical
proficiencies, it is extremely important for a
business to invest in IT infrastructure by adding
processors with computing power and large
databases (Chen, Chiang & Storey, 2012).

Issues Faced Contd..
 Problem with Big Data Value: The big data value
issue is the next significant issue that is common for
big data. As huge investments are required for
ensuring data privacy, several organizations cannot
afford this technology and value is not created
(Constantiou & Kallinikos, 2015).
 Handling of Voluminous Data: During handling of
voluminous data, it becomes quite common that
data privacy is being lost (Wu et al., 2014).

Conclusion
Therefore, conclusion can be drawn that big data privacy
is an important aspect that is needed to be considered for
bringing effectiveness and efficiency in social media.
Complexity of data sets is managed in a better manner so
that decision making process is improved. The most
common example of big data technology is Hadoop,
which helps to store large data amount. There are several
issues that are required to be considered while
understanding big data privacy. Social media platforms
like Facebook and Twitter can be secured with big data
technology.

Recommendations for dealing with
Big Data Privacy Issues in Future
The suitable recommendations to any social media
website for dealing with the big data privacy issues in
future are as follows:
 Implementation of Machine Learning: The
technology of machine learning is one of the most
significant technologies for dealing with big data
privacy issues in future in an efficient manner. This
is possible as machine learning helps to prepare
data and then conduct predictive analysis.

Recommendations Contd..
 Data Scientists: Data scientists or analysts should
be involved in the business so that the big data
issues could be resolved in future effectively.
 Buying Algorithms and not Buying software:
The third recommendation to any business for
dealing with the big data privacy issues in future
would be buying algorithms instead of buying
software. This would ensure that users’ data is
being used effectively.

References
 Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS
quarterly, 36(4), 1165-1188.
 Constantiou, I. D., & Kallinikos, J. (2015). New games, new rules: big data and the changing context of strategy. Journal of
Information Technology, 30(1), 44-57.
 Eckhoff, D., & Sommer, C. (2014). Driving for big data? Privacy concerns in vehicular networking. IEEE Security &
Privacy, 12(1), 77-79.
 Kaisler, S., Armour, F., Espinosa, J. A., & Money, W. (2013, January). Big data: Issues and challenges moving forward. In 2013
46th Hawaii International Conference on System Sciences (pp. 995-1004). IEEE.
 Kallinikos, J., & Constantiou, I. D. (2015). Big data revisited: a rejoinder. Journal of Information Technology, 30(1), 70-74.
 Katal, A., Wazid, M., & Goudar, R. H. (2013, August). Big data: issues, challenges, tools and good practices. In 2013 Sixth
international conference on contemporary computing (IC3) (pp. 404-409). IEEE.
 Kshetri, N. (2014). Big data׳ s impact on privacy, security and consumer welfare. Telecommunications Policy, 38(11), 1134-
1145.
 Lu, R., Zhu, H., Liu, X., Liu, J. K., & Shao, J. (2014). Toward efficient and privacy-preserving computing in big data era. IEEE
Network, 28(4), 46-50.
 Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In 2013 International Conference on Collaboration Technologies
and Systems (CTS) (pp. 42-47). IEEE.
 Sharma, R., Mithas, S., & Kankanhalli, A. (2014). Transforming decision-making processes: a research agenda for
understanding the impact of business analytics on organisations. European Journal of Information Systems, 23(4), 433-441.
 Victor, N., Lopez, D., & Abawajy, J. H. (2016). Privacy models for big data: a survey. International Journal of Big Data
Intelligence, 3(1), 61-75.
 Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE transactions on knowledge and data
engineering, 26(1), 97-107.
 Xu, L., Jiang, C., Wang, J., Yuan, J., & Ren, Y. (2014). Information security in big data: privacy and data mining. IEEE Access, 2,
1149-1176.
 Yu, S. (2016). Big privacy: Challenges and opportunities of privacy study in the age of big data. IEEE access, 4, 2751-2763.
 Zhang, D. (2018, October). Big data security and privacy protection. In 8th International Conference on Management and
Computer Science (ICMCS 2018). Atlantis Press.