Big Data Privacy: An Examination of Issues, Benefits, and Future

This report provides a comprehensive analysis of Big Data privacy, exploring its definition, importance, and benefits within a business context. It delves into the challenges and major issues associated with privacy problems in Big Data, such as data breaches and security risks. The report examines the characteristics of Big Data, including volume, variety, and velocity, and how they affect privacy. It discusses the importance of data privacy, explores technologies, and the need for privacy preservation mechanisms. The report highlights benefits like time and cost effectiveness and better decision making. It concludes with three recommendations to address future privacy concerns, emphasizing the need for robust data protection measures and ethical considerations.

Running head: BIG DATA PRIVACY
Big Data Privacy
Name of the Student
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Author’s Note:

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Table of Contents
1. Introduction...............................................................................................................2
2. Discussion................................................................................................................2
2.1 Defining Big Data and Big Data Privacy.............................................................2
2.2 Understanding Importance of Privacy in Big Data in Business..........................4
2.3 Major Benefits of Technologies Big Data and their Privacy...............................6
2.4 Major Issues confronted for Privacy problems in Big Data.................................8
3. Conclusion..............................................................................................................10
4. Three Recommendations to deal with Issues of Big Data Privacy in Future.........11
References.................................................................................................................13

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1. Introduction
A significant field, which is majorly responsible for treating with various
methodologies towards effective analysis, organized information extraction and also
dealing with the most complex and complicated data sets that cannot be easily dealt
with existing traditional data processing software application due to its larger size
(Kitchin, 2014). Big data could even be featured by three distinctive characteristics or
3Vs. These 3Vs refer to data volume, variety and velocity. Amongst them, first V is
volume, which eventually deals with huge data volume and this helps to measure the
volume for determining size of the data set or data (Harford, 2014). Variety or
second V refers to broader or wider distinct types of data that are required to be
managed by the organization.
The final or third V is the velocity, which refers to subsequent velocity of data,
at which the data must be processed in an effective way by respective user. The
entire technology of big data can be stated as quite safe as well as secured and thus
this technology can be utilized by various companies to reduce the complexity of
large data sets (Assunção et al., 2015). This report will be outlining a detailed
description on the wide topic of privacy in big data technology. The subsequent
importance, benefits or risks to use big data and how these affect privacy aspect will
be well depicted in the report. Furthermore, three appropriate recommendations
would even be provided in this report.
2. Discussion
2.1 Defining Big Data and Big Data Privacy
One of the most promising technologies that is being used for perfect usage
of predictive analytics, advanced methods towards data analytics and even user

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behaviour analytics for extracting subsequent value from data for a specific data set
and data size is termed as big data (Zaslavsky, Perera & Georgakopoulos, 2013). A
perfect and detailed analysis of every data set can also search for the new and
important correlations to spot all types of trends in business, disease prevention,
eradication of unethical or illegal crime and several others. Each and every business
executive, advertisement agency and government can remove the various issues or
problems by undertaking major help from the large data sets in subsequent and
important areas for business informatics, searching of information and few others
(Khoury & Ioannidis, 2014). Each of these data set mainly grows rapidly within the
business since they are being gathered by few effective devices of Internet of things
such as remote sensors, cameras, wireless sensor networks, software log and few
others (Jin et al., 2015). Several significant companies, who are owning major
initiatives of big data mainly affect the complete business as well as business related
procedures.
The data with huge volume can originate from various important and
significant sources such as business transactions systems, customer’s database,
machine generated information, real time data, mobile application and social
networks that are quite popular to be used within significant environment of the
technology of internet of things (Dong & Srivastava, 2013). All of the data are being
left in raw form and are also previously processed by ensuring help from data mining
tools and data preparation software so that it is better analysed effectively and
efficiently. As the technology of big data has the core responsibility of dealing with
any type of large set of data that consists of more varied as well as complex
structure and it is needed for eventually considering all the major aspects of security
and privacy (Kim, Trimi & Chung, 2014). Since this technology of big data requires

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high power of computation and large storage, some of the most important distributed
systems could be used. Several parties would eventually be included in these
systems and thus the risk to violate security and privacy issues is highly
incremented.
Various mechanisms of privacy preservation are being developed, which can
be extremely effective and efficient to protect and also to ensure security at every
stage like data generation, data storage and even data processing regarding the
entire big data life cycle (Demchenko et al., 2013). Since, this specific big data
technology can reveal any type of hidden pattern easily and can also identify the
secret correlations, few significant issues related to privacy are being considered in a
business (Crawford, 2013). For the recent technological development, the data that
is being generated by sensor networks, social networking sites, applications of
health care industry, social networking websites and many more are increasing
regularly. This type of potential breach in privacy can also be incremented for the
factor and power driven by the technology of big data, storage and re usage of data
as privacy issues of big data well as gathering of information are also being done for
gaining profit within any organization (Najafabadi et al., 2015).
2.2 Understanding Importance of Privacy in Big Data in Business
The privacy aspect of big data termed as an important and significant feature,
which is needed for analysis based on priority. The various data of the users might
be subsequently breached after following some hacking techniques (Hu et al., 2014).
The personal information are also breached when it is being amalgamated with any
type of external data set and hence leading to interference of some facts about
users. These types of facts are also known as the secretive facts and thus they must
not be eventually revealed to other users for the purpose of maintaining

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confidentiality to a high level (Chen & Lin, 2014). Furthermore, this type of personal
information could even be sometimes gathered and used in a business to add major
value to business. This type of sensitive data even is stored as well as processed in
a specified non secured location for avoidance of data leakage in the first two stages
of data life cycle, which are storing and data processing (Lee et al., 2013).
To ensure privacy in big data, there are some of the major and the most
significant mechanisms being developed within the recent times. These important
mechanisms can also be grouped based on the several phases of the life cycle of
big data (Hampton et al., 2013). To protect data privacy, the respective
organizational access should be eventually restricted and several techniques of data
security must be utilized in an effective manner. The most important and significant
techniques for this type of data access restriction eventually ensure that these data
are not released or provided to non trusted parties. Various significant privacy
protection and security approaches in data storage phase are mainly selected on the
basis of few significant encryption techniques (Wamba et al., 2015). Such effective
techniques of encryption mainly involve identity based encryption, storage path
encryption and attribute based encryption. Furthermore for ensuring that the
confidential information is secured and safe, organizations even use hybrid clouds,
where they store confidential information. Moreover, they use amalgamation of
hybrid and private clouds (Constantiou & Kallinikos, 2015). The entire stage of this
processing of data also includes privacy preserving data publishing or PPDP for
ensuring that correct and relevant knowledge are being extracted.
The privacy of big data is quite vital since every major issue of data
processing as well as theft of data and these are needed to be eradicated on time.
Better maintenance of the technology of big data for dealing with type of data issue,

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thus making business and business processes proper and appropriate (Chen,
Chiang & Storey, 2012). This technology also offers storage capabilities and huge
power processing. Hadoop is one of the most popular applications of big data that
can perform tasks that are extremely difficult to the various conventional systems.
Furthermore, the big companies often eradicates this technology of big data as they
become unable to remove the privacy issues and hence precautions are also
undertaken by them (Ketter et al., 2015). A popular and common issue in this case is
outsourcing that increases capital as well as operational expenses to higher level.
Therefore, each and every organization should consider about the major issues and
how to deal with them to bring more success in the company.
2.3 Major Benefits of Technologies Big Data and their Privacy
Few important and noteworthy benefits or advantages are present that make
the entire technology of big extremely efficient and effective (McAfee et al., 2012). As
it is responsible for dealing with both unstructured and structured data, big data is
quite popular for each and every business or company. Maximum information is
being obtained and thus extra support and process of decision making are being
enhanced during this procedure (Manyika et al., 2011). Furthermore, it even provides
a potential for using data efficiently, hence making data accessible for the
businesses from external sources before analysing them for to obtain various
advantages (Kallinikos & Constantiou, 2015). Any type of privacy issue in a business
can even be dealt effectively so that business is able to obtain several opportunities
for creation of new growth methods.
Few important and noteworthy benefits of big data technologies and privacy
are provided below:

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i) Time Effectiveness: Big data is extremely time effective and it does not
incur any type of extra time for executing the processes (Sharma, Mithas &
Kankanhalli, 2014). The several high speed tools of big data involve Hadoop and
memory analytics help in easier identification of new data sources, which could be
helpful for data analysis and for making faster decisions.
ii) Helps to Develop New Products: Another benefit of big data for any
business is that it is used to develop several new products after understanding
customers’ demands and market trends (Waller & Fawcett, 2013). This is done by
predictive analytics and thus bringing innovation and creativity within organization.
Each and every requirement of customer is easily met with this technology.
iii) Market Conditions Well Understood: Big data even does analysis for
understanding the present market conditions by knowing about customers’
purchasing behaviours and thus helping out the business in finding out regarding
several products according to the trend (Chen & Lin, 2014). Big data even helps in
getting competitive advantages for all customers.
iv) Better Management of Data: The technology of big data helps in better
data management and hence eliminates niches so that any business is able to gain
better overview of clients after involvement of calculated metrics.
v) Better Decision Making Process: The entire process of decision making
is highly enhanced by the significant involvement of big data and thus the quality of
decisions gets improved (Kim, Trimi & Chung, 2014). Furthermore, thus type of
process is also effective to eradicate the major issues faced in current situation and
hence involving several procedures to manage decisions.

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vi) Cost Effectiveness: Big data is extremely cost effective and it does not
involve any type of extra cost while implementation. The various tools like Hadoop
and cloud based analytics comprise of the advantage of bringing various cost
benefits and thus identifying several effective methods to do business (Khoury &
Ioannidis, 2014). For this cost effectiveness, any specific business never faces
issues and thus implementation is much easier in comparison to other technologies.
2.4 Major Issues confronted for Privacy problems in Big Data
Significant data with numerous rows can offer high statistical power, although
higher complexity data can lead to higher false discovery rate. Big data helps to
describe regarding large volumes of semi structured, structured and unstructured
data that comprise of a major potential to be mined for obtaining information and
getting used in some machine learning projects or even few advanced analytics
applications (Zaslavsky, Perera & Georgakopoulos, 2013). Various important and
complex streams of data in any unprecedented speed must be eventually dealt in
timely manner and without incurring delay. The sensors, smart metering as well as
radio frequency identifier tag can have the responsibility to drive basic requirement of
dealing with several torrents of data within real time (Demchenko et al., 2013). As
per the final aspect of the technology of big data, variety, organizational data can
come in numerous data formats such as numeric or structured data in traditional
databases into subsequent unstructured data format like audio, emails, financial
transaction, unedited text documents, video and data from stock ticker (Hu et al.,
2014). All types of complexities regarding data handling are highly reduced and thus
big data has become extremely popular in all types of businesses like hospitality,
health care, financial sector and several others.

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In spite of the fact there are few important and specific benefits of this
technology of big data, some of the core issues and complexities would also be
present and such distinctive issues are provided below:
i) Main Issue with Privacy and Security: The most important and significant
issue, which is being confronted for the subsequent presence of the technology big
data within business (Lee et al., 2013). All types of emerging applications of big data
technology majorly emphasizes on privacy and security issues. Furthermore,
organizations that are bigger in size often face several issues of privacy and security
after big data is being successfully implemented in the business. For avoiding this
specific privacy and security issue, various significant organizations often seek into
developing and maintaining several important big data capabilities after putting
investments on protocols, processes and infrastructure and thus having a core
objective to protect confidential data and then eradicate these risks related to
security (Chen, Chiang & Storey, 2012).
ii) Major Requirements and Challenges in Technology: This is the second
significant issue faced due to privacy problems in big data. This specific technology
requires major capabilities regarding data processing and even technical
proficiencies (Ketter et al., 2015). Since the organization comprises of a core
capacity to mine large volumes of data, these users require investing on IT
infrastructure that consist of the processors with significant computing power, IT
capability and large databases. Furthermore, the users also need a proper
competency degree that has allowed them in addressing several problems regarding
data storage, management of database, quality assurance, and scalability in
infrastructures, access and transportation of data and many more (Kallinikos &
Constantiou, 2015).

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iii) Problems with Big Data Value: Another issue that is common here is the
major problem with subsequent value of big data. A proper persistence for concern is
being present over original value of organization and for the purpose of resolving all
challenges and response to big data deployment responses, higher investments are
required (Waller & Fawcett, 2013). Hence, it is not possible for all businesses to
afford the expenses and large organizations can develop big data capabilities,
however small business cannot invest money in this phenomenon.
iv) Handling any type of Large Volume Data: This is the fourth distinctive
issue that is common for privacy problems within big data technology. Since they
have to deal with the complicated sets of data, handling of large volume data could
be extremely problematic for the business (Kim, Trimi & Chung, 2014). Moreover, for
handling this type of bulky data, risk of loss of data is quite high.
3. Conclusion
Hence, from this above provided discussion, conclusion can be drawn that the
technology of big data can be referred to as an important and significant term that
helps to describe regarding huge volume of structured, semi structured as well as
unstructured data. These data types are responsible for deluging a specific
organizational in a periodical manner. The big data can also be effectively analysed
for some of the major insights, leading to more effective or efficient decision making
process and even strategic business movements. The respective data volume even
refers to the core factor that every organization has the capability of collecting data
from various sources such as business transaction, social media as well as
confidential data from sensor and data from machine to machine.

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There are some of the core and important big data technologies such as Big
Data Analytics and Hadoop, which could easily and promptly store huge data
amount and various types of data to ensure that velocity and variety of data are
being maintained for dealing with the data complexity. This above report has
properly demonstrated about the factor that big data is extremely important for any
business sector and it comprises of numerous advantages and risks. Finally, three
relevant recommendations are being described in the report to ensure that big data
privacy issues are resolved in future efficiently.
4. Three Recommendations to deal with Issues of Big Data Privacy in Future
Three suitable and appropriate recommendations for any specific business to
deal with the privacy issues of big data in near future are provided below:
a) Implementing Machine Learning Technology: One of the major and the
most significant and suitable recommendation to any particular organization for
dealing with the respective privacy issues of big data in near future would be proper
implementation of machine learning technology. Machine technology is also referred
to as one of the major forefront for revolution of big data. It is extremely useful or
helpful for any organization to eventually prepare the most confidential data and
afterwards conducting a proper predictive analysis. This type of analysis can allow
the respective users to eradicate such privacy issues of big data in future in a better
manner.
b) Not Dependent on Software: This is the second important and significant
recommendation to a specific user of big data for dealing with privacy issues of big
data in near future efficiently and effectively. The respective organizations or users
must buy their typical algorithms and not solely being dependent on the software