Big Data & Privacy

The report analyzes the in-depth concepts of Big Data & Privacy, the issues and solutions to overcome them, and provides a secure Big Data platform. It also provides cultural issues and resolution to those issues and finally with a positive solution and strategy for implantation.

Running head: BIG DATA & PRIVACY
Big Data & Privacy
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Executive summary
The term Big data is used for the set of large data whose structure are varied and complex. The
characteristics are correlate which have difficulties in analyzing, storing and applying for
procedure and results to get extract. The analytics of Big Data have complex data that is describe
in this report. The report contains the analysis of the big data issues and the solution to the issues
in order to overcome from the problem and provide a secure Big Data platforms.

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Table of Contents
Introduction......................................................................................................................................3
Analysis...........................................................................................................................................3
Cultural Issues – Issue Resolution...................................................................................................4
Positive solution and strategy for implantation...............................................................................5
Conclusion.......................................................................................................................................7

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Introduction
The term Big data is used for large and complex data sets were applications having
traditional data processing are inadequate. It consists of data capturing, analysis zing, searching,
data creation, transfer, storage capacity, querying, visualization and information privacy
(Crawford and Schultz 2014). Large datasets are collected for Big Data which could not be
processed adequately with the use of traditional processing techniques (Xu et al. 2014). Big Data
uses various frameworks, tools and techniques. It describes both the structured and unstructured
data which could be easily adapted in the day-to-day business environment. The data that the
organization utilizes is what matter mainly. This report will analyze the in-depth concepts so that
better decisions and strategic were taken for the organization development (Kshetri 2014). Thus,
the report will analyze Big data for various organization and utilize them for the privacy and
security purpose. It will also provide some cultural issues and resolution to that issues and finally
with a positive solution and strategy for implantation.
Analysis
Various organization draw big data analytics were services are not utilizing due to the
absence of protection tools for privacy and standard security. In this section, it has been analyzed
that the platforms for big data has upgrade all the possible strategies that are helpful for privacy
protection (Inukollu, Arsi and Ravuri 2014). The strategies have a framework that supports:
 The policies monitors the generation of productive enforcement.

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 The generated monitor had integration into the target analytics platforms. The traditional
DBMS become inadequate due to the big data context were the execution have
necessities that are needed to handle volumes of large data, data heterogeneity and
analyzed the data speed.
 The privacy policies have some specification that could manage data access that could be
stored for big data platform.
Data having large amount are collected and generated from the agencies of business and
government. Opportunities are getting created for increase focus with substantial sum of data for
understanding the opportunities and avenues in order to understand the data process for varying
domains (Perera et al. 2015). The big data potential come with a price, the privacy of the user is
at danger always. The terms and regulations of the privacy ensure conformance for the big data
analytics and mining practices. The applications are kept verify by the developers that could
conform the privacy agreements and the information that are sensitive are all kept private
regardless of privacy regulations. The challenges could be address by identifying the need with
new contributions that have formal methods and testing procedures.
Cultural Issues – Issue Resolution
In terms of Big data privacy and security is an important concern. The model of Big data
security could not be suggested for the complex applications where it get disabled by default.
Moreover, in the absence of Big data privacy, data get compromised easily. Some privilege
being provided to information that have privacy concern in order to use and collect personal
information (Jain, Gyanchandani and Khare 2016). A group or individual have got some capacity
of privacy for information which stop information about themselves for the known people. The

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privacy issue of the user identifies the personal information through the internet transmission.
The information and the asset of information is defended through the use processes, training and
technology to avoid disclosure, disruption, inspection, recording, modification and destruction.
The governance and use of individual data through data privacy that set up the policies to
ensure the personal information of the consumers’ that are collected, utilized and shared in some
appropriate ways. For Big data, security mainly concentrate in data protection from malicious
attacks and stolen data misuse for their profit. Security becomes fundamental while protecting
data were privacy is not sufficient to be address.
Positive solution and strategy for implantation
A Big data analytic solutions could be provided when the organization perform some
complex analytics for the unstructured data in order to optimize the processes, unlock the value
of the data and deliver real-time insights. For the future events, advance analytics solutions is
very much helpful to make the decisions faster and better through various techniques like risk
analytics, operational analytics and customer value analytics (Mehmood et al. 2016). It is a good
think to delight the customers with personalized experience with the use of analytic solutions.
With this solution the organization could keep track of the behavior of the consumer as it offers
recommended products that have dynamic discounts with pleasant and happy experience of
shopping. The complete overview of the supply chain enterprise has generated the solutions for
big data analytic by embracing the inventory levels, identifying the potential issues of backlog
and fulfill the needs of the product.
The collection of complex structured and unstructured data in large amounts are protected
were data has a non-authorized access. The most common solution included here is encryption

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that could make the data secure regardless of whether the data has been resided in computer, data
center, or mobile devices. The Big Data need a holistic security vision, different sources of data,
and data access that has been allowed. The security mechanisms closer to the data sources
provide security right and prevention and control mechanisms, control the access and prevention
of data leakage that need to be work together. The Big data ensure data trustworthiness in the
entire lifecycle of the data for the usage till the collection. The technology for secure encryption
need to be employed to protect data that are confidential. Homomorphic encryption allows
computations that are specific to ciphertext and could generate an encrypted result.
Most of the renowned Company have Big Data and Analytics Solutions which provides
analytic solutions that are reliable and effective. This simplify the IT infrastructure, innovate the
models of the business and have processes that accelerate the business. While entering into the
world of Big Data multiple sources are integrated for both internal and external data that
generate 360-degree view of the consumer (Moura and Serrão 2015). Augmenting could be
provided for cyber security for risk identification, fraud detection and data streams that have
real-time incoming or outgoing monitoring. The decision making could be improve in order to
understand, visualize and discover all enterprise data while they are explored. The encryption
through homomorphic enables searching on data that are encrypted were the user could store
files that are encrypted on a remote file server which can satisfy the Boolean constraint. The
multiparty computation is secure as the efficiency is improve by homomorphic encryption. The
processing and storage of encrypted data is related by Big Data that have security and privacy
challenges. The data security infrastructure continuously improves the aspect of analyzing,
monitoring and learning and leverage the solutions for the existing security.

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Conclusion
From the above study it could be concluded that Big data is the new era for gathering and
storing data in huge amount. The paper could present the challenges of privacy and security that
has affected the Big Data projects. If the methodologies, tools and practices could not ensure the
security and privacy then they are ineffective to use in an integrated manner. Through proper
analysis better advances were made in many enterprises. The challenges that were introduce by
access control, security, encryption, compression and compliance are addressed in a systematic
way. However, the environment of computing become cheaper, and analytics environments are
shared over cloud. Thus, the paper has highlighted the privacy issue of the Big Data and analyses
has been made based on that. In order to secure the computing infrastructure and processing of
Big Data, the problem of privacy and security need to be addressed.

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References
Crawford, K. and Schultz, J., 2014. Big data and due process: Toward a framework to redress
predictive privacy harms. BCL Rev., 55, p.93.
Inukollu, V.N., Arsi, S. and Ravuri, S.R., 2014. Security issues associated with big data in cloud
computing. International Journal of Network Security & Its Applications, 6(3), p.45.
Jain, P., Gyanchandani, M. and Khare, N., 2016. Big data privacy: a technological perspective
and review. Journal of Big Data, 3(1), p.25.
Kshetri, N., 2014. Big data׳ s impact on privacy, security and consumer
welfare. Telecommunications Policy, 38(11), pp.1134-1145.
Mehmood, A., Natgunanathan, I., Xiang, Y., Hua, G. and Guo, S., 2016. Protection of big data
privacy. IEEE access, 4, pp.1821-1834.
Moura, J. and Serrão, C., 2015. Security and privacy issues of big data. In Handbook of research
on trends and future directions in big data and web intelligence (pp. 20-52). IGI Global.
Perera, C., Ranjan, R., Wang, L., Khan, S.U. and Zomaya, A.Y., 2015. Big data privacy in the
internet of things era. IT Professional, 17(3), pp.32-39.
Xu, L., Jiang, C., Wang, J., Yuan, J. and Ren, Y., 2014. Information security in big data: privacy
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