PRIVACY IN BIG DATA ASSIGNMENT HELP

1. Introduction

In contemporary condition of global business, introduction of newer technologies in organisation became mandatory. Without implementing proper technology in various business processes, business entities generally, face competitive disadvantages. In recent global business process, big data plays an essentially important role regarding processing of information. Main motive of this study is to enlighten several factors regarding privacy of big data in several business contexts. In global context, it is seen that cyber security regarding big data possesses great deal of threats and compromise of big data is a great loss for a company. This chapter of the study sheds light on significant of the research work and evaluates aims and objective of research work.

In current concept of global business process, this research work on big data privacy is essentially significant. Through the process of this study, researcher emphasised on privacy problems of big data and its impact on business processes of companies is also properly mentioned. Cyber security regarding big data possesses great deal of threats and compromise of big data is a great loss for a company.  On the other hand, introduction of big data has also several beneficiary factors that help an organisation to gain competitive advantage in the industry. Therefore, this study has essential materials which aid the needs of global organisation regarding knowledge big data security and implementation.

This contemporary research work on big data privacy has followed a distinctive method through which important analytical works on cyber security problems of the companies use big data has been done. Several benefits that companies can avail through implementing big data in their business process are also established through proper examples and data analysis process. The concept of big data came in business industry is introduced recent time therefore there are very limited resources on big data security system. The originality of this research work can be seen through proper information and analysed data on big data privacy which is crucial for business entities in need of proper knowledge regarding big data.

The Parable of Google Flu: Traps in Big Data Analysis

Ahn, Kim and Chung (2014, p.260) mentioned that trapping big datais the substitute of trapping the traditional data and performing its analysis. It is interesting because it requires advanced technology with new strategies. By using the advanced method, the researcher cannot ignore the different types of fundamental issues. Douet al. (2015, p.460) opined that the fundamental data is the original approach of Big Data analysis which includes different statistical measurements, validity construction along with its reliability and data dependencies. The most challenging part is the advanced technology instrumentation output are not always valid in nature for scientific analysis. Thus, the researcher new proposal is to follow the old strategies during data analysis but with the help of advanced technology. The combination of the old strategy in advanced technology is called the hybridization procedure. By following the hybrid procedure the resource requirement is minimised along with time. The results include the big data size minimization for which more research and development required. Study of different types of the algorithm is constantly changing the strategies. So the researcher must replicate their data finding across time in a robust pattern. Ahn, Kim and Chung (2014, p.260) mentioned that instead of the big data revolution, the researcher must focus on the all data revolution.

A survey on security and privacy issues in big data

Cloud computing which is an advanced and powerful technology that helps to perform a large and complex scale data. The rapid growth of the network services through internet increase the amount of data. Every industry is trying their level best to come up the enormous data. Big data is not only difficult to keep and store the huge data along with their analysis. It also challenging to maintain the security and privacy of their data in order minimize the breach of data. The interesting part of cloud computing is it eliminates the need for expensive computing hardware along with dedicated space and software. The researcher proposed to combine the cloud computing along with big data. The big data generally provides user about the commodity computing to a different process. In the result, the user needs the resultant sets of output data of analysis. Cloud computing is a section of data-processing platforms. Lazeret al. (2014, p.1205) argued that big data needs additional requirements for maintaining the security and privacy of the data while gathering, analysing, storing and transferring due to network traffics.  The IT department gives the permission to the employees to access the data. The combination of both the big data and cloud computing can analyse large data in a short period of time. The result is in different types of analytical graphs for different cases decision making. This combination provides facilities for different computation and procedure facilities for research purposes. The infrastructure of the cloud computing can easily come up with the new strategy for data analysis. Jagadishet al. (2014, p.90) argued that the lack of sufficient data gives cluster types of result. However, by applying the combined method of big data and cloud computing the transition of data in a result is performed correctly.

Securing the Big Data Life Cycle

Douet al. (2015, p.460) opined thatBig data can be used to create health-related significant value by improving the results and lower the costs. The main features of the big data are it has the capacity to handle the massive data at high velocity. The recent proposal of the big data is to create large data analysis. The big data measures the different data related to the health problem, workflows by the NGO, tools required to analyse the data of the different health-related issues. Big data measures the new diseases in a new way, which brings benefits to the society as well as to the business purposes. More or less maximum pharmaceutical companies are struggling to keep the record of their business related data. Sagiroglu and Sinanc (2013, p.45) commented that the IT executives managing the enormous data through the help of big data which gives stability to their problems. It brings a successful data security to the companies and big data easily keep the records in such a manner that it can be access data easily later on if required. Jagadishet al. (2014, p.90) stated that the advantage of using the big data is it can bring open source data software where anybody can see the essential data. It can secure the data according to the command of the IT executives. The open and close data can be both access by the authorised person only. The other pharmacy company also performs sometimes breach of data. Lazeret al. (2014, p.1205) argued that this breach of data can be easily controlled by the big data. It also gives security to the data along with its accessible analysis. Potential pitfalls of it are the companies are focused on their potential benefits instead of securing their data. The open data allows its competitor to compete easily with their pitfalls which are included in the open data. The present revenues, the income status etc are not included in the open source data.

Douet al. (2015, p.460) opined that Cloud security deals with the large infrastructure, diversity of different data and formats. The two third of the security products are protected by the big data.this prevents the breaches of the company server which used to occur frequently than the network. 

Meeting the challenges of big data

Big datadelivers the significant efficiencies and benefits to the society and it deals also with the scientific research, health, environment etc. Ahn& Chung (2014) mentioned that it is highly useful for storing and accessing a large amount of data. It provides confirmed data, which helped for further research and development. The information in Big data is not always private. Gaff et al. (2014) commented that data generated here regarding natural and atmospheric conditions like pollution. It can also deal with the human behaviour regarding health issues. In short, it is very versatile in nature. But sometimes by the help of the open sources breach of information occurs. This helps the competitors of the company to improve their negative impacts and can raise their business prospects. Jagadishet al. (2014) stated that during the emergency, one can track the revenue models of the companies in order to see the online activities. Such online tracking can be performed by the authorised person only. Big data is also used by the companies during marketisation of their products through online. These reduce the financial risks which are generally occurred during advertising. The challenges and risks it raises are the serious concerns on the total impact of dignity along with rights and freedoms, which includes the right of privacy.  

Ahn& Chung (2014) mentioned that the imbalance between the information of the open and private sites and fall the business. By using the updated data higher hierarchy can predict the pitfalls. This prediction helps to identify the negative impacts and according to with it, the researcher can perform the research and development to increase the demand for the products. The recent research helps to create the innovate products which help to meet the customer demands. The transparency of the automated decision also increases the demand for big data. The different product description helps the customer to understand about the product quality. This advertisement of product through online the customers can easily distinguish the product of different brands. Gaff et al. (2014) commented that Data protection department deals with the black box. The black box includes the negative impacts of the companies open sources for which the companies face a huge problem. The data protection departments deal with all the information of the companies and they decide how to progress and disclose the different information to the open source in suitable time. Jagadishet al. (2014) stated that traditional policies safeguard the personal data. But here due to open source on big data the company are very much conscious about their data sharing in their open sites. Lazeret al. (2014) argued that enterprises spend a lot of money and effort to create innovative products and in the same way, it has to spend a lot of money to protect the useful information. Luet al. (2014) stated that big data need a lot of research and development to protect the company's updated strategies. 

 

It is mentioned in the process that the concept of big data is introduced in recent time therefore certain knowledge big data process in companies are limited which created problems for the research work. On the other hand, journals and books that has been used for the research work has limited information regarding application and privacy problems of big data as they are full with conceptual information of big data.

Main motive of this research work is to find out several issues regarding privacy in the context of Big data and to find out several mitigating factors to overcome these challenges. Objectives of this research work are:

Objectives

  • To identify security of big data in business context
  • To analyse Big data privacy and sensitivity
  • To investigate several issues related with privacy of big data
  • To recommend several factors to mitigate privacy concern of using big data

Evaluating objectives of the research work, proper research questions are also established. These questions are:

Questions

  • What are security measurements of big data in context of business?
  • What is big data privacy?
  • What are main issues related with big data privacy?
  • What are mitigating factors for privacy related issues of big data?

Research Onion

1.png

Figure 1: Research Onion

(Source: Saunder, Lewis, & Thornhill, 2009).

Research Philosophy

According to Creswell (2013),in order to conduct this research work, the researcher follows Positivism Philosophy.  Positivism philosophy demands analytical research work with availability of proper logic which is essentially important in order to find out proper information regarding big data privacy in organisations. All knowledge on big data creates positive impact on this research work which is main theme of positivism philosophy. Research Approach

In order to conduct this research work, researcher follows deductive research approach. Creswell (2013)opined that ,  the concept of deductive approach mentions that main motive of this kind of research work is to analysis a testing theory and evaluate result for the research work form that existing knowledge. This process of research approach is properly followed in this research on big data privacy and positive results of research work indicate that deductive approach of research work was essentially useful.

Research Design

Descriptive design is essentially important in order process whole research work through a smart and efficient way. Creswell & Poth (2017), opined thatdescriptive design mentions three different processes in order to conduct the research work. Through this research work, different cases studies are properly analysed in order to evaluate perfect information regarding big data privacy.

In order to collect proper information regarding big data privacy Secondary Qualitative method is followed by researchers. Irwin (2013), mentioned that through this process, data has been collected by thematic analysis of available articles on big data. In order to conduct the whole research work proper way 8articles from online sources are collected and important information regarding big data privacy are collected from. There are several benefits regarding secondary data analysis as it is essentially easy to access through online medium. Most of the journals and articles are unpaid versions therefore acquiring this process is essentially low cost. On the other hand, through this process, research work is done properly aligning with research questions.

Researcher in order collect online articles for research purpose has followed a certain criteria. These articles are all written in English and properly peer reviewed. On the other hand, from proper and authentic database, researcher has selected these articles. All these articles are recently written and all of them are essentially authentic.

Attribute Name

Data Type

Description

Security Measures in Big data

Secondary Qualitative (Article)

Big data is one of the most important assets in modern companies. According to Moreno, Serrano & Fernández-Medina (2016),it is seen that implementation of Big data has enhanced the business process of a company but it has drawbacks also as data security is one of the most common threats among these companies.

 

Attribute Name

Data Type

Description

Big data Challenges and Opportunities

Secondary Qualitative (Article)

On the other hand, big data privacy is essentially important for companies and it creates several opportunities for them. It is mentioned through a recent survey that companies like IBM consider big data as a game changer and 82 percent of market believes on that. It is also mentioned that 40 percent problems of a company related to problems of poor data management.

 

Attribute Name

Data Type

Description

Privacy Issues of Big Data

Secondary Qualitative (Article)

Privacy issue is one of the most burning issue which can be seen in most of the business entities. Improvement in technology is also increases the threats of data theft threats of hackers also are increasing day by day.

 

Theme 1:Security Measures in Big Data

Security measurement while using big data in industries is a huge concern for an organisation. In several contexts, it is seen that organisations use security measurement in several approaches of an organisation. According to Moreno, Serrano & Fernández-Medina (2016),it is mentioned that most of business organisations use security measurement on Infrastructure security system and Data privacy security system. According to the researcher more than 74 percent of organisations use security measurement on these aspects.

Use of Security Measurement

Percentage

Infrastructure Security

38%

Data Privacy

37%

Data Management

15%

Reactive and Integrity Security

10%

 

On the other hand it is mentioned in Open Security Foundation regarding Dataloss DB project, it is mentioned that data loss incidents has been categorized through different processes. Schmitt et al. (2014, p. 2), opined that in more than 57 percent of cases, data has been lost through the involvement of external parties. 10% percent of overall data loss cases happened due to involvement of internal parties and 20% of data loss happened due to accidental causes.

 

Causes of Data Losses

Percentage

External Cause (hacking, theft)

60

Internal Cause

10

Web related loss

10

Accidental cause

20

 

Table 2: causes of Data Loss

( Source: Zicari, 2014)

 

 

Theme 2: Big data Challenges and Opportunities

According to Khan et al.(2014), business organisations mostly face challenges in processes like Data growth, Data infrastructure, Policy of data, data integration, data variety and velocity, regulation of data and data visualisation.

 

Challenges

Percentage

Data growth

30

Data infrastructure

12

Policy of data

15

data integration

14

data variety

10

velocity

9

regulation of data

12

data visualisation

8

 

Table 3: Challenges of Big Data

 

 

On the other hand, big data privacy is essentially important for companies and it creates several opportunities for them. According to Simo et al. (2011, p. 2), it is mentioned through a recent survey that companies like IBM consider big data as a game changer and 82 percent of market believes on that. It is also mentioned that 40 percent problems of a company related to problems of poor data management.

Theme 3: Privacy Issues of Big Data:

Privacy issue is one of the most burning issues which can be seen in most of the business entities. It is mentioned by Jaseena & David (2014), that improvement in technology is also increases the threats of data theft threats of hackers also are increasing day by day. It mentioned that more than 70 percent of data are being theft through several hacking activities and 30 percents of them are breached through fraud web accounting.

 

Threats of Privacy breach

Percentage

Hacking process

70%

Fraud Web Accounting

30%

Table 4: Threats of Privacy breach

(Source: Schmitt, 2013).

 

 

 

According to Colombo et al.(, p. 2), several organisation uses languages like UML, EMF and OCL modelling languages in order to increase privacy policy of big data. It is seen that most of the organisation use OCL.


Use of Modelling Language regarding Big Data Privacy (Globally)

Percentage

OCL

63

UML

21

EMF

16

 

Julio Moreno et al. (2016), that most of business organisations use security measurement on Infrastructure security system and Data privacy security system, mention it in the article. According to the researcher more than 74 percent of organisations use security measurement on these aspects. While acquiring information regarding big data Challenges and Opportunities regarding big data privacy it was found that big data privacy is essentially important for companies and it creates several opportunities for them. According to Simo et al. (2011, p. 2), it is mentioned through a recent survey that companies like IBM consider big data as a game changer and 82 percent of market believes on that. It is also mentioned that 40 percent problems of a company related to problems of poor data management. Privacy issues regarding big data is one of the most important theme as it conveys information regarding main objective of the research work. It mentioned that more than 70 percent of data are being theft through several hacking activities and 30 percents of them are breached through fraud web accounting. According to Colombo et al.(, p. 2), several organisation uses languages like UML, EMF and OCL modelling languages in order to increase privacy policy of big data. It is seen that most of the organisation use OCL.

Through the process of data analysis, it is seen that in modern era, big data has its global presence. First theme of data analysis deals with security measures of big data where it is mentioned that all around the globe; companies are facing major problems regarding security in big data system. It was mentioned that more than 74 percent of organisations use security measurement on infrastructure security system which reflects high concerns of organisation regarding big data security. In second theme, challenges and opportunities through big data privacy are mentioned. Problems like poor data management can be solved through this process as it is mentioned that IBM consider big data as a game changer and 82 percent of market believes on that. It is also mentioned that 40 percent problems of a company related to problems of poor data management. In third theme privacy issue and several mitigating steps practised in several institutions are mentioned.  Several organisationsuse languages like UML, EMF and OCL modelling languages in order to increase privacy policy of big data. It is seen that most of the organisation use OCL.

Through this whole research process a certain method is properly followed by the researcher. Through the process important information regarding big data privacy is properly highlighted. In contemporary condition of global business, introduction of newer technologies in organisation became mandatory. Without implementing proper technology in various business processes, business entities generally face competitive disadvantages. In recent global business process, big data plays an essentially important role regarding processing of information. Goal of this research work is to identify important information regarding big data privacy and this process is done through proper steps. In introduction stage aim objectives and research questions are properly mentioned. In the section of literature review, important aspects regarding big data in business organisation is mentioned. Researcher has followed secondary qualitative data analysis where three themes are introduced. First theme of data analysis deals with security measures of big data where it is mentioned that all around the globe; companies are facing major problems regarding security in big data system. Second theme, challenges and opportunities through big data privacy are mentioned. In third theme privacy issue and several mitigating steps practised in several institution are mentioned. On the other hand, several mitigating factors regarding challenges of big data privacy also mentioned.


 

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