Big Data Analytics And Its Ethical Implications: A Study

Fundamental Project Goal

The fundamental goal of the proposed study is to identify the trends and tools that are revolutionising the Big Data analysis and its potential impact on the Big Data analytics associates that includes the users and the customers of the users. The paper will also focus on the ethical aspect of current and coming trends in big data.

The discussed project is aimed at identifying the trending tools that are and will revolutionise the big data analytics and in the process of identification, the author will gain an insight into the subject. Furthermore, the project will also consider the ethical implications that the new trends may have on the big data and its associates, which will assist the studier in his professional life. Understanding of the ethical implications will enable the author to use the technology with proper ethical consideration.

Big Data and new trends in it is the subject of major for the author so understanding of the technology so that he will be ready for the professional world. The project has provided the author to enhance his skills and knowledge in the big data and relevant field. It has opened up paths for new learning and skill development. Furthermore, identification of the ethical implications will help the author to develop himself as an ethical professional, which will develop credibility in the corporate world. Additionally, proper execution of the project will enable the author to seek attention from employers as a professional of big data. The reasons discussed above are the most prominent reason for the interest of the author in the discussed area. Apart from the above mentioned reasons, the increasing size of data and hence, the need for big data is a factor for attraction and hence, the interest.

Another reason for the interest over the area of research is the case of Facebook Cambridge Analytics where, Facebook sold the data of its users and Cambridge used the data for decipher the interest and perception of the geographic dominated Facebook users (Issak & Hanna, 2018). The discussed case have been analysed in different case studies however, no proper attention has been cited on the potential misuse of the big data analytics technology. Hence, to mitigate similar further potential misuse of the technology it is crucial to identify its ethical implications so that proper framework for the use of the technology can be developed. So, one of the factors that inspired the project is the case of Facebook Cambridge Analytics.

Big data is one of the major technological developments of the current era because of the prominence offered by it. Big data refers to large sets of data that could be analysed using different computational techniques so that trends, patterns along with associations relevant to human interaction and behaviour could be identified (Wu et al., 2014). The findings from the big data analytics is used by the firms to develop strategic plan of the firm taking account of the employee. Hence, it would be justified to state that the big data analytics is playing prominent role in the advancement and productivity of a firm.

Statement of Major

The need for big data is crucial because it is estimated that over 2.7 Zeta bytes of data is currently available on the digital universe and it is very difficult to analyse such huge size of data even in small chunks through traditional analysis method. The above stated fact is at a global level context however; on an individual basis, also the data are very large. The above-mentioned statement could be supported by the fact that Google processes more than 40,000 searches everyday while Walmart manages 1 million transaction data every hour. Similarly, Facebook witness 300 million photos upload everyday with 510000 comments and 293000 status updates all of which contributes to the data size of the organisation’s database (Huda et al., 2018).  Hence, processing such huge chunks of data to identify patterns, preferences and other factors is very crucial for human analysis or traditional modes of analysis. The discussed need can be simplified with big data analytics because it has been developed for analysis of huge chunks of data. Furthermore, the capability of big data analytics is not limited to analysis of huge data but future extends to analysis of data in details along with offering recommendations based on the identified patterns and frameworks.

The primary focus of the proposed study will be focused on identification of the trends and tools that are revolutionising the Big Data analysis and its potential impact on the Big Data analytics associates that includes the users and the customers of the users. So, as part of the study different activities need to be performed and some question needs to be answered. The questions that needs to be answered includes:

1. What is Big Data Analytics and its role in organisation?
2. What are the trends and tools that are and will drive the use of Big Data Analytics by its users and potential users?

• What impact will the identified trends and tools will have on the Big Data users and its customers?

1. Are the current and upcoming trends ethical in nature?

To answer the questions successfully that had been discussed above certain activities needs to be undertaken. The activities will include:

1. Review of the secondary work and pattern identification.
2. Background establishment

• Selection of sample and population

1. Development of questionnaire for data collection
2. Data collection
3. Data analysing and summary

• Deriving conclusion
• Report Development.

The activities listed above needs to be undertaken to answer the questions that the study will attempt to answer. The first activity that will be undertaken will be the review of the secondary sources because the review will reflect on certain findings that will assist the studier to understand the subject and the knowledge that is available in context to the subject. The secondary sources in discussion refers to the scholarly studies that had been assessed in past or present over the subject along with newspaper & magazine articles, blog posts by reliable firms, government publications and similar others. The identifications will not only assist in understanding subject but will also reveal certain facts based on which questionnaire for the collection of the primary quantitative data will be developed. The questionnaire will then be distributed among 20 Big Data professionals and based on the responses received; the analysis of the data will be done. The sampling of the professionals will be done based on the random sampling and the population will be from the geographical domain of the proposed study.

Post collection of the data, the quantitative data will be analysed with descriptive or inferential analysis (based on the collected data). As part of the analysis MS Excel will be used for (descriptive only) and SPSS (for both descriptive and Inferential). The selection of the tools can be justified by the fact that the discussed are the most reliable tools for academic researches and study. Furthermore, the availability of the tools is also simple as they are available at nearly all University’s lab and even the student version is available for the tools. The analysed data will then be compared and contrasted with the findings from the review. The results from the compare and contrast will then be used for answering the questions using the critical thinking and brainstorming of the studier. Finally, the study will be summarised to conclude on the paper. Finally, a proper report will be developed for the presenting the study and its findings.

Background

The completion of the project will deem need for certain crucial skills that includes both technical and non-technical skills. As part of the technical skills, expertise of certain tools will be necessary. The tools in discussion includes, MS Word for the report presentation, Google Forms for the development of questionnaire that will be used for the collection of data, MS Excel for the storing and processing of data and SPSS for inferential analysis. MS word is well versed by the studier however, proper skills regarding the SPSS, MS Excel and Google Forms needs to be developed and it will be developed from the free tutorials over the tools that are available on free media sharing sites such as YouTube, Dailymotion, Twitch and Vimeo. Furthermore, the expertise available at the university will also be asked for assistance. The author should also have a high level of internet awareness so that the he can differentiate between the reliable-trustworthy sources and untrustworthy publications on the internet. The author possesses the above-discussed skill but for further assurance, only trusted search engines will be used.

As part of the non-technical skills, the author will need the skills of researching, communicating, maintaining unbiased attitude, and similar others. The researching skills will be used for identifying important articles, journals and other reliable sources as part of the secondary data. The communication skill will be used for communicating with the participants of the survey and the individuals who will offer guidance for the discussed project. Non-verbal communication will be preferred over verbal because the participants will be communicated through non-verbal means such as email or instant messaging services. Unbiased attitude is not a skill rather an approach but is crucial for the project. It will ensure that the researcher will not manipulate data to offer a biased result from the project.

Anticipated Outcomes

The outcome anticipated from the project will be diverse in nature that includes:

1. Findings from the secondary sources and the survey.
2. Answers to the questions that the project will discuss.

• One of the most crucial finding from the project will be the ethical aspect of the big data usage. The discussed finding has been considered as one of the most crucial because in recent times it has been identified that the firms are using the capability of big data for fulfilling personal objectives and agendas, which is evident from Facebook Cambridge Analytics case.

1. A summary of all the efforts, discussion and findings in the form of the report.

The resources required for the project can be classified in two categories that includes materialistic (M) and non-materialistic (N) resources. The table presented below presents the resources that will be required for the success of the project.

Budget and approach are the most prominent limitations that may influence the outcome of the project. The limited budget will restrict the author from collecting the most relevant data and the outcome may be compromised. The limited approach of the author can also act as a limitation because then the expertise that the author requires for the successful delivery of the project may be compromised. Furthermore, limited approach may also lead to inclusion of less knowledgeable individual as part of the survey that will compromise the outcome. Limited access to the library resources will also act as a limiter for the project.

The table attached below have presented the timeline that is estimated for the project in discussion. The crucial activities along with the duration and the estimated time it will consume has been detailed in the table. However, it should be noted that the timeline presented is estimation and may alter from the proposed time line based on determined data and findings. Most time of the study will be dedicated to the review of the literary works and the data analysis so that the output from the study are accurate, reliable and feasible.

TITLE OF RESEARCH- Identification of new trending tools for big data analysis 

The aim of the project is to identify the trends and tools that are revolutionising the Big Data analysis and its potential impact on the Big Data analytics associates that includes the users and the customers of the users. The project will also focus on the ethical aspect of current and coming trends in big data.

The outcome of the project will help to develop the users of big data to get an insight into the new trends and tools. Furthermore, identification of the ethical aspect of the big data will assist in development of strategies to mitigate the threat that is being faced by the customers of big data users.

The data collected as part of the project will stay limited to the studier and will not be shared with any other individual. Only one copy of the data will be stored in the system of the data collector and no further copies will be developed. The data will not be converted in any non-electronic state to protect the identity of the participants. Finally, only limited personal data will be collected that is crucial for the project and no additional data will be collected.

The collected data will only be used for academic purpose and no commercial use of the data will be done. Furthermore, manipulation of the data will also be avoided so that the outcome of the project is reliable and ethical in nature. 

References

Huda, M., Maseleno, A., Atmotiyoso, P., Siregar, M., Ahmad, R., Jasmi, K., & Muhamad, N. (2018). Big data emerging technology: insights into innovative environment for online learning resources. International Journal of Emerging Technologies in Learning (iJET), 13(1), 23-36.

Isaak, J., & Hanna, M. J. (2018). User Data Privacy: Facebook, Cambridge Analytica, and Privacy Protection. Computer, 51(8), 56-59.

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.

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