Big Data Essays (Examples)
Study Document
CFOs Big Data Opportunities In Firms
Introduction
The growth of big data has had significant transformative effects on several industries including technology, agriculture, health, education, and finance. Over the past decade, the number of humans … agriculture, health, education, and finance. Over the past decade, the number of humans using smartphones has increased tremendously and this has created a big pool of user data as smartphone users stamp their digital footprint all over the web. The electronic data collected as a result of these activities yield big data that provide valuable insights to decision-makers looking for data points to inform their decision processes. The growth of big data has necessitated the development of computer algorithms and tools that can analyze the data at scale. Good analysis and interpretation of the data allow organizations to ‘co-create’ solutions alongside their target users and create new value that is highly tailored to the needs of the market … to……
References
References
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS quarterly, 36(4).
Jin, X., Wah, B. W., Cheng, X., & Wang, Y. (2015). Significance and challenges of big data research. Big Data Research, 2(2), 59-64.
Joshi, N. (2018). How Big Data Can Transform the Finance Industry. Retrieved October 7, 2019, from https://www.bbntimes.com/en/technology/big-data-is-transforming-the-finance-industry .
Nath, T. I. (2019). How Big Data Has Changed Finance. Retrieved October 7, 2019, from https://www.investopedia.com/articles/active-trading/040915/how-big-data-has-changed-finance.asp .
Turner, D., Schroeck, M., & Shockley, R. (2013). Analytics: The real-world use of big data in financial services. IBM Global Business Services, 27.
Yin, S., & Kaynak, O. (2015). Big data for modern industry: challenges and trends [point of view]. Proceedings of the IEEE, 103(2), 143-146.
Zhou, K., Fu, C., & Yang, S. (2016). Big data driven smart energy management: From big data to big insights. Renewable and Sustainable Energy Reviews, 56, 215-225.
Study Document
Clinical Informatics
… work. This is no less true in the field of health care, where clinical informatics is reshaping the nursing workplace environment, how patient data is recorded and shared, and how health care is delivered. This paper will discuss clinical informatics concepts emerging in the 21st century, what … nurses need to know how to engage in information retrieval, the way librarians do. They need to be able to plug information into data, pull up information from other data, search for information manage knowledge effectively. Additionally, they have to be able to appraise information. When conducting an information search in a data, they may get a return of a thousand different references or sources of information. If they cannot process that information and appraise it … it is also about how to appraise information and assess its value. Keeping complete records for the purpose of electronic medical records (EMR) data……
References
References
Cho, O. M., Kim, H., Lee, Y. W., & Cho, I. (2016). Clinical alarms in intensive care units: Perceived obstacles of alarm management and alarm fatigue in nurses. Healthcare informatics research, 22(1), 46-53.
Effken, J., Weaver, C., Cochran, K., Androwich, I., & O’Brien, A. (2016). Toward a central repository for sharing nursing informatics’ best practices. CIN: Computers, Informatics, Nursing, 34(6), 245-246.
Elsayed, W. A., Hussein, F. M., & Othman, W. N. (2017). Relation between nursing informatics competency and nurses’ attitude toward evidence-based practice among qualified nurses at Mansoura Oncology Center. International Journal of Nursing Didactics, 7(6), 26-33.
Drolet, B. C., Marwaha, J. S., Hyatt, B., Blazar, P. E., & Lifchez, S. D. (2017). Electronic communication of protected health information: privacy, security, and HIPAA compliance. The Journal of hand surgery, 42(6), 411-416.
Haupeltshofer, A., Egerer, V., & Seeling, S. (2020). Promoting health literacy: What potential does nursing informatics offer to support older adults in the use of technology? A scoping review. Health Informatics Journal, 1460458220933417.
Kharbanda, E. O., Asche, S. E., Sinaiko, A. R., Ekstrom, H. L., Nordin, J. D., Sherwood, N. E., & O’Connor, P. (2018). Clinical decision support for recognition and management of hypertension: a randomized trial. Pediatrics, 141(2).
Khezri, H., & Abdekhoda, M. (2019). Assessing nurses’ informatics competency and identifying its related factors. Journal of Research in Nursing, 24(7), 529-538.
Kleib, M., & Nagle, L. (2018). Factors associated with Canadian nurses\\\\\\\\\\\\' informatics competency. CIN: Computers, Informatics, Nursing, 36(8), 406-415.
Study Document
Barriers That Prevent Implementation Of IoT Within Small Businesses
… operate their businesses, and current trends indicate that these implementations are increasing exponentially. The Internet of Things allows conventional computer-based networks to incorporate data collected from everyday objects to provide real-time analyses and new applications for these technologies are being developed every day. Indeed, there are already … literature in chapter two. Chapter three provides a detailed description of the study’s qualitative methodology and chapter four presents the results of the data analysis. Finally, chapter fives provide a summary of the research together with answers to the study’s guiding research questions and subquestions.
The Implementation … into the foreseeable future (Haghshenas & Richards, 2016). In other words, the Internet is here to stay – at least until the “next big thing” comes along to replace it – and software engineers and IT professionals are hard at work to exploit these technologies even further, … work to exploit these technologies……
References
References
Ahamed, J., & Rajan, A.V. (2016). Internet of Things (IoT): Application systems and security vulnerabilities. 2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA), 1-5.
Aishah, S., Sahandi, R., Prakoonwit, S., & Khan, W. (2019). Big data and IoT opportunities for small and medium-sized enterprises (SMEs). In Handbook of Research on Big data and the IoT. doi: 10.4018/978-1-5225-7432-3.ch005
An, N. & Wang, J. (2018, October). Research and practice on innovative methods of ideological and political education for college student. Educational Sciences Theory and Practice, 18(5), 2386-2391.
Banham, R. (2016, July-August). IoT complexity: As the Internet of Things expands, the risks-and questions of liability-become more complicated. Risk Management, 63(6), 39-44.
Bhardwaj, A., Subramanyam, G. V., Avasthi, V. & Sastry, H. (2016). Review of solutions for securing end user data over cloud applications. International Journal of Advanced Computer Research, 6(27), 2277-2291.
Bok, H. (2014, September). An empirical study on factors influencing Internet advertising effects. Advances in Management, 7(9), 6-9.
Business.com. (2018). Disaster preparedness for small businesses. Business.com, September 26. Retrieved from https://www.business.com/articles/business-disaster-prep/ .
Cass, J. (2019). Internet of Things: What it is, how it works, examples and more. Just Creative. Retrieved from https://justcreative.com/2018/11/19/internet-of-things-explained/ .
Study Document
Privacy In Social Networks Regarding Machine Learning
… how machine learning protocols have been developed both to enhance and secure privacy as well as to invade privacy and collect, analyze, predict data based on users’ information and experience online. The conflict between these two directions in machine learning is likely to lead to a system … to lead to a system wherein machine learning algorithms are actively engaged in the subversion of one another, with one attempting to conceal data and the other attempting to uncover it. This paper concludes with recommendations for social networks and the issue of privacy regarding machine learning.
… concludes with recommendations for social networks and the issue of privacy regarding machine learning.
Introduction
Social networks have allowed an ocean of personal data to form that is now sitting there waiting for machine learning algorithms to collect it, analyze it, and recognize individuals on social media … social media (Oh, Benenson, Fritz……
References
References
Balle, B., Gascón, A., Ohrimenko, O., Raykova, M., Schoppmmann, P., & Troncoso, C. (2019, November). PPML\\\\\\\\\\\\'19: Privacy Preserving Machine Learning. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security (pp. 2717-2718). ACM.
Bilogrevic, I., Huguenin, K., Agir, B., Jadliwala, M., Gazaki, M., & Hubaux, J. P. (2016). A machine-learning based approach to privacy-aware information-sharing in mobile social networks. Pervasive and Mobile Computing, 25, 125-142.
Bonawitz, K., Ivanov, V., Kreuter, B., Marcedone, A., McMahan, H. B., Patel, S., ... & Seth, K. (2017, October). Practical secure aggregation for privacy-preserving machine learning. In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security (pp. 1175-1191). ACM.
Hunt, T., Song, C., Shokri, R., Shmatikov, V., & Witchel, E. (2018). Chiron: Privacy-preserving machine learning as a service. arXiv preprint arXiv:1803.05961.
Lindsey, N. (2019). New Research Study Shows That Social Media Privacy Might Not Be Possible. Retrieved from https://www.cpomagazine.com/data-privacy/new-research-study-shows-that-social-media-privacy-might-not-be-possible/
Mohassel, P., & Zhang, Y. (2017, May). Secureml: A system for scalable privacy-preserving machine learning. In 2017 IEEE Symposium on Security and Privacy (SP) (pp. 19-38). IEEE.
Mooney, S. J., & Pejaver, V. (2018). Big data in public health: terminology, machine learning, and privacy. Annual review of public health, 39, 95-112.
Oh, S. J., Benenson, R., Fritz, M., & Schiele, B. (2016, October). Faceless person recognition: Privacy implications in social media. In European Conference on Computer Vision (pp. 19-35). Springer, Cham.
Study Document
Digital Era And Taxation
… principle because of it difficult to pin down how and where digital companies create value. Also, digital companies rely heavily on intangible assets, big data, and which is hard to value (Sand- Zantman, 2018). Given this fact, there is a need to research problems that tax accountants face ……
References
References
Committee of Experts on International Cooperation in Tax Matters. (2019). Tax Issues related to the Digitalization of the Economy: Report (E/C.18/2019/CRP.12). https://www.un.org/esa/ffd/wp-content/uploads/2019/04/18STM_CRP12-Work-on-taxation-issues-digitalization.pdf
Katz, R. (2015). THE IMPACT OF TAXATION ON THE DIGITAL ECONOMY. https://www.itu.int/en/ITU-D/Conferences/GSR/Documents/GSR2015/Discussion_papers_and_Presentations/GSR16_Discussion-Paper_Taxation_Latest_web.pdf
Pemerathna, A. (2016). Economic impact of digital taxation: A case on information communication technology industry Sri Lanka. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2910328
Sand-Zantman, W. (2018). Taxation in the Digital Economy. https://www.orange.com/fr/content/download/47110/1371114/version/1/file/Rapport%20TAXATION-VF-Mai2018.pdf
Sestakova, M. (2018, February). Tax Challenges of the Digital Economy [Paper presentation]. Management Challenges in the 21st Century, Bratislava, Slovakia.
Study Document
Nursing Informatics In Education
… knowledge of informatics would be helpful since the industry itself is trending ever increasingly towards an informatics-centric way of nursing. One of the big challenges that Kinnunen et al (2017) identify is the lack of eHealth knowledge and its benefits among educators and students alike. What this … focusing on based on technology trends in the healthcare industry include the use and understanding of electronic health records (EHRs), wearable technologies, and big data and data analytics. Risling (2017) also notes that student nurses require more opportunities to study a wide range nursing informatics issues.
Clearly it can be … enter nursing school at the college level.
The Impact
Introducing informatics early on in…[break]…stage of students’ academic careers. Google Scholar is an online data search engine that was used: key words associated with the subject were entered in and titles and abstracts of returns were analyzed to … arranged and……
References
References
Eardley, D. L., Krumwiede, K. A., Secginli, S., Garner, L., DeBlieck, C., Cosansu, G., & Nahcivan, N. O. (2018). The Omaha System as a Structured Instrument for Bridging Nursing Informatics With Public Health Nursing Education: A Feasibility Study. CIN: Computers, Informatics, Nursing, 36(6), 275-283.
Kinnunen, U. M., Rajalahti, E., Cummings, E., & Borycki, E. M. (2017). Curricula challenges and informatics competencies for nurse educators. Forecasting informatics competencies for nurses in the future of connected health, 232, 41-48.
Piscotty Jr, R. J., Kalisch, B., & Gracey?Thomas, A. (2015). Impact of healthcare information technology on nursing practice. Journal of Nursing Scholarship, 47(4), 287-293.
Risling, T. (2017). Educating the nurses of 2025: Technology trends of the next decade. Nurse education in practice, 22, 89-92.
Shackelford, S. (2019). Industry Voices—Healthcare is changing. We need to reach the future workforce earlier. Retrieved from https://www.fiercehealthcare.com/hospitals-health-systems/industry-voices-healthcare-changing-and-our-educational-approach-should-be
Shin, E. H., Cummings, E., & Ford, K. (2018). A qualitative study of new graduates’ readiness to use nursing informatics in acute care settings: clinical nurse educators’ perspectives. Contemporary nurse, 54(1), 64-76.
Tubaishat, A. (2019). The effect of electronic health records on patient safety: A qualitative exploratory study. Informatics for Health and Social Care, 44(1), 79-91.
Study Document
Supply Chain Management In Ethiopia
… chain. Specifically, the authors look at the challenges as they apply to manufacturing firms in Ethiopia. The authors used semistructured interviews to obtain data. Participants worked in both export and import markets. Interviews were spread across nine different manufacturing industries in Ethiopia. The industries included the alcohol … different manufacturing industries in Ethiopia. The industries included the alcohol industry, the garment industry, wood industry, textile, leather, food, and ceramics industries.
The big challenge facing these firms is simply the fact that technology has not advanced in the developing world to assist with supply chain integration. … all still using telephone, verbal instructions and letters to relay information. There was no use of digital technology to facilitate and enhance communication. data collection was all paper based, which means that information processing is extremely slow compared to what is possible in the developed world.
Thus, … was all paper based, which……
References
References
Afshan, N. (2013, December). The performance outcomes of dimensions of supply chain integration: A conceptual framework. Business: Theory and Practice, 14(4), 323.
Georgise, F. B., Thoben, K. D., & Seifert, M. (2014). Supply chain integration in the manufacturing firms in developing country: An Ethiopian case study. Journal of Industrial Engineering, 2014.
Prensky, M. (2001). Digital natives, digital immigrants part 1. On the horizon, 9(5), 1-6.
Spiess, J., T'Joens, Y., Dragnea, R., Spencer, P., & Philippart, L. (2014). Using big data to improve customer experience and business performance. Bell labs technical journal, 18(4), 3-17.
Study Document
How Amazon Hedges Its Forex Risk
… Amazon tends to adopt the same pricing strategy as in the US, and one of the tricks it uses is to leverage its data. Amazon changes prices on products frequently, based on a broad range of variables including profit margins, inventory, competitors’ prices, shopping patterns and a … including profit margins, inventory, competitors’ prices, shopping patterns and a wide of other input variables (Mehta, Detroja & Agashe, 2018). Amazon uses this data for things like loss lead pricing, in the hopes that consumers will start to think that Amazon’s prices overall are good. The complexity … prices overall are good. The complexity of Amazon’s pricing strategy is mirrored in other countries, but is obviously better in countries where sufficient data exists to make solid data-driven decisions. The prices are set in local currency, as well, but the frequent changes may take into account foreign currency fluctuations in some ………
References
References
Amazon 2019 Annual Report. Retrieved April 29, 2020 from https://s2.q4cdn.com/299287126/files/doc_financials/2020/ar/2019-Annual-Report.pdf
HowMuch.net (2019) Charting the most powerful reserve currencies in the world. HowMuch.net. Retrieved April 29, 2020 from https://howmuch.net/articles/worlds-top-reserve-currencies-2019
Mehta, N., Detroja, P. & Agashe, A. (2018) Amazon changes prices on its products about every 10 minutes – here’s how and why they do it. Business Insider. Retrieved April 29, 2020 from https://www.businessinsider.com/amazon-price-changes-2018-8
Reiff, N. (2020) Hedge. Investopedia. Retrieved April 29, 2020 from https://www.investopedia.com/terms/h/hedge.asp
Roamy (2019) The consequences of Amazon’s pricing power. Medium.com. Retrieved April 29, 2020 from https://medium.com/goods-services/https-medium-com-goods-services-amazons-pricing-power-797e28b63fbd
Statista (2019) Annual net sales of Amazon in selected leading markets from 2014 to 2019. Statista. Retrieved April 29, 2020 from https://www.statista.com/statistics/672782/net-sales-of-amazon-leading-markets/
Study Document
Intelligence Oversight Ethics
… revelations, Wizner (2017) affirms that the nation’s institutions and organizations have altered the ways and have swung from collecting every piece of digital data on Internet users to being more mindful of the privacy rights of persons: from courts to Congress to media firms and technology companies, … to be seen was how and in what manner that authority would be carried out.
Technology also improved, which made the gathering of big data a major opportunity for intelligence agencies to gather as much information on people as they possibly could. This was a game changer for … have shown how the recent technological developments have led to a quantitative and qualitative breakthrough in Signals Intelligence” but also how “the mass data gathering plans of the NSA and its American and British partners” were being used to spy on companies and individuals who were not … least because they begged……
References
References
Bailey, Christopher and Susan M. Galich. “Codes of Ethics: The Intelligence Community.” International Journal of Intelligence Ethics 35.2 (2012), 77-99.
Brown, William F., and Americo R. Cinquegrana. \\\\\\\\\\\\"Warrantless Physical Searches for Foreign Intelligence Purposes: Executive Order 12,333 and the Fourth Amendment.\\\\\\\\\\\\" Cath. UL Rev. 35 (1985): 97.
Cantarella, Michele. \\\\\\\\\\\\"Intelligence ethics in the digital age.\\\\\\\\\\\\" (2016).
Congressional Research Service, “CIA Ethics Education: Background and Perspectives” (2018).
Ferrari, Rachel. \\\\\\\\\\\\"Moral Relativism and Dangerous Ethical Dilemmas in the US Intelligence Community.\\\\\\\\\\\\" (2018).
Ford, Christopher M. \\\\\\\\\\\\"Intelligence Demands in a Democratic State: Congressional Intelligence Oversight.\\\\\\\\\\\\" Tul. L. Rev. 81 (2006): 721.
Goldman, Jan. \\\\\\\\\\\\"Teaching About Intelligjence and Ethics.\\\\\\\\\\\\" Journal of US Intelligence Studies 20, no. 2 (2013): 79.
Hayes, Jonathan. \\\\\\\\\\\\"The Cinema of Oliver Stone: Art, Authorship and Activism by Ian
Study Document
Manufacturing Systems In Automotive Industry
… automation can guarantee the production line to be significantly safer for personnel by organizing robots to tackle hazardous situations. More so, incorporating automated data gathering can enable the firm to gather key manufacturing information, enhance data precision, and diminish data gathering expenses (Lamb, 2013).
Production Machine
The majority of the manufacturing process in automotive manufacturing systems is carried out by machines in some ……
References
References
Boone, L. E., Kurtz, D. L., & Khan, M. H. (2009). Contemporary business. Hoboken: John Wiley & Sons.
Chui, M., George, K., Manyika, J., Miremadi, M. (September 2017). Human + machine: A new era of automation in manufacturing. McKinsey & Company.
Deng, W., Luo, Q. (2012). Advanced Technology for Manufacturing Systems and Industry. New York: Pearson.
Groover, M. P. (2007). Fundamentals of modern manufacturing: materials processes, and systems. John Wiley & Sons.
HR Cloud. (2020). HR Automation - The Future of Human Resource Process Management. Retrieved from: https://kissflow.com/hr-process/
Joshi, V., Adhikari, M. S., Patel, R., Singh, R., Gehlot, A. (2018). Industrial Automation: Learn the current and leading-edge research on SCADA Automation. New Delhi: Pearson.
Krar, S. F., & Gill, A. (2003). Exploring advanced manufacturing technologies. Industrial Press, Inc.
Ladet, P., & Vernadat, F. (Eds.). (2013). Integrated manufacturing systems engineering. Springer.
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