IMAT5262 : Research, Ethics & Professionalism in Computing

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MScInformationSystemsManagementPxxxxxxxxDe Montfort UniversityDO NOT INCLUDE YOURNAME AS THE WORK WILLBE ANONYMOUSLY MARKEDAssignment - Project ProposalEthics in Big DataIMAT5262 Research, Ethics& Professionalism inComputing
P Number: PxxxxxxxxIMAT5262 Research, Ethics & Professionalism inComputingAbstractIn the contemporary business scenario, big data is of immense importance forbusiness organizations, as management of business organizations with theassistance of big data is able to make effective decisions and formulate appropriatestrategies. In this regard, the aim of the proposed research study will be tounderstand the usage of big data, Characteristics of big data, business benefits ofbig data, and challenges organizations face while using big data and data analytics.The proposed study will aid in seeking relevant information about big data and itsimportance for business organizations in the contemporary business environment.The study will further assist managers, business personnel and academic students inunderstanding the importance of big data for business organizations to performeffectively in the electronic markets. Additionally, the study will facilitate indetermining the role of customer satisfaction towards business performances andsuccess. The findings obtained from the proposed study will facilitate in acquiringgreater competitive advantages by identifying the needs and preferences of thecustomers as well as the behavior of competitors.Key WordsBig data, data analytics, online survey, Ethics, competitive advantage.1
P Number: PxxxxxxxxIMAT5262 Research, Ethics & Professionalism inComputingTable of Contents1.Background................................................................................................................................32.Research questions.................................................................................................................33.Literature Review......................................................................................................................43.1 Examples of Companies using Big Data..........................................................................43.2 Characteristics of Big Data..................................................................................................63.3 Advantages of Big Data........................................................................................................73.4 Challenges of Big Data.........................................................................................................74.Methodology Review................................................................................................................84.1 SECTION 1 - REVIEW....................................................................................................................84.2 SECTION 2 – SELECTION....................................................................................................95.Conclusion.................................................................................................................................96.References...............................................................................................................................107.APPENDICES...........................................................................................................................12Appendix (A): Project Plan...........................................................................................................12Appendix (B): Ethical Review Form.............................................................................................0Appendix (C): Consent Form.........................................................................................................5Appendix (D): Pilot study................................................................................................................72
P Number: PxxxxxxxxIMAT5262 Research, Ethics & Professionalism inComputing1.Background“Big Data” as its name indicates is a collection of huge amounts of formless andmeaningless data which are generated by high-quality and heavy softwareapplications belonging to a varied group of software applications such as socialnetworks, a wide variety of scientific computing applications, medical informationsystems, e-government applications, and many more. The research has shown thatdata that is used and processed by these different software applications share somecommon attributes(Davis & Patterson, 2012). Some of these commoncharacteristics can include large-scale data (which defines the distribution and sizeof data stores), scalability issues (it define the functionalities and features softwareapplications processing across-the-board, huge data repositories such as big data).Scientific computing is believed to be one of the most important application areas forthe reason than in this domain academic researchers and scientific create hugeamounts of data every day in the results of their experiments and tests (for instanceconsider fields such as astronomy, high-energy physics, biomedicine, biology andmany others). On the other hand, extracting valuable information and knowledge fordifferent useful tasks on the basis of these huge, comprehensive data stores seemsto be impracticable for common database management systems and other similaranalysis tools2.Research questions(i)What are the common characteristics of Big Data?(ii)Identify the advantages and challenges associated with the use of BigData.(iii)Review literature on Big Data.3
P Number: PxxxxxxxxIMAT5262 Research, Ethics & Professionalism inComputing3.Literature Review3.1 Examples of Companies using Big DataWhen dealing with big data, there are two important things that are usually taken intoaccount; data generation and data analytics. Data analytics deals with the analysis ofdata and occur at two levels. Level 1 deals with data collection and regenerationwhile level 2 is predictive and prescriptive(Feinleib, 2014).Disney has invested 1 million dollars in data in data generation and handling. Theyhave developed a wrist pin that is given to customers and it collects data and relaysit to a large central server where it is analyzed. This data is used in marketing andimproving customer service (Wang, 2017). IBM, on the other hand, has invested 24billion dollars in data analytics and through a company called Watson has employedabout 15000 analytical practitioners to handle data collection and analysis. This datais used to analyze the market and improve their business. Another example on theuse of data analytics in business is the BMW motor company whereby a surveyconducted showed that people who were getting into cars were always having theirwindows broken in winter as a result of ice accumulation (Xu & Zhou, 2015). In orderto improve the customer confidence in their product, the company took it upon itselfto wash the parked cars and give them back to the customers whenever they wantedto leave. In this way, the customer confidence in BMW improved. Facebook usesdata analytics to conduct surveys and improve their business and the quality ofservice they offer to their customers(Fontichiaro, 2018). Recently, Facebookconducted a survey asking the question of which gender between males andfemales spends more time sharing photographs on Facebook and the data collectedshowed that women spend more time sharing photographs than men. About 350million photographs were shared daily on Facebook.According to (Walker, 2015), for one to become a data scientist he must have datahandling skills such as programming, databases creation and analysis, mathematicalmodeling, statistical analysis and above all he must be creative. If we analyze thetrend on the use of big data by big companies, it is evident that companies arehesitant in investing in big data. About 55-60% of the investments in big data fail.This can be attributed to the fact that the companies start on technology first ratherthan an understanding of the understanding of the fundamentals of the business(Yadav, 2017).4
P Number: PxxxxxxxxIMAT5262 Research, Ethics & Professionalism inComputingToday, there is a very high demand for data in business performance and marketanalysis and hence the need for companies to invest in big data. However, a majorsetback in handling big data is the shortage of data scientists to work in this field.This comes in as a challenge to education institutions to train experts to work in thislarge data(Frampton, 2015).Data mining entails the process of collecting and analysing large data volumes ordata sets in order to discover their respective relationships. On the other hand, theterm, ‘Big data’ describes a massive structured and unstructured data volume, whichis so complex to process using the common or traditional database and technicalsoftware functionalities.It is very essential to note that a deep scrutiny of real world commercialimplementation of data, makes the International Business Machines (IBM) come outas one of organizations with a high quality ‘Big data’ hub. At this company’s ‘Bigdata’ hub, large volumes of information are handled, which are actually very hard toprocess in a traditional database. The data hub is composed is of data miningengines integrated to aid in easy handling of data.The integration of data mining in IBM has made very easy and fast for the companyto manage and process data in its globally placed (using cloud technology) immensedata warehouses. Thus, this makes it clear that although the data is large, it isrealistically the simplest and easily tolerable data volumes in data mining. In thissense, I hereby agree that the term ‘Big data’ is actually an over-hyped buzzword fordata mining.Microsoft Incorporation is one of the most successful software companies globally.Due to the large data volumes handled at the company, the subject of ‘Big data’ inthe company has also been a subject of concern. At this company, issues related to‘Big data’ have usually been experienced in scenarios where the organization’straditional database system is exhausted with the ever-increasing data volumes. Thisincludes operating system files, cache files, customer data and managementinformation system data. However, through the adoption of data mining engines,Microsoft Incorporation has smoothly been handling all the large amounts of datathat it shares globally with clients and partners. Therefore, this case study furthermakes me agree with the statement.5
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