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ACCENTS Transactions on Information Security (TIS)

ISSN (Print):XXXX    ISSN (Online):2455-7196
Volume-7 Issue-27 July-2022
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Paper Title : Unlocking the power and unveiling the challenges of big data management and analysis: insights from diverse domains
Author Name : Om Prakash and Sandhya Gawade
Abstract :

The multifaceted realm of big data was investigated in this paper, encompassing its management and analysis across diverse domains. The pivotal role of big data in sectors like healthcare, education, competitive intelligence, and the Internet of Things (IoT) was explored. The integration of advanced analytics, cloud-based solutions, and innovative techniques such as deep learning and artificial intelligence was examined. Moreover, potential challenges, including scalability concerns, integration complexities, publication bias, attribute relationships, and dimensionality reduction evaluations, were identified in the study. By shedding light on the advantages and limitations of big data analytics, this research contributed to a comprehensive understanding of its implications in contemporary society.
Keywords : Big data management, Data analytics, Healthcare, Education, IoT.
Cite this article : Prakash O, Gawade S. Unlocking the power and unveiling the challenges of big data management and analysis: insights from diverse domains . ACCENTS Transactions on Information Security. 2022; 7 (27): 17-22. DOI:10.19101/TIS.2022.725015.
References :
[1]Li W, Chai Y, Khan F, Jan SR, Verma S, Menon VG, et al. A comprehensive survey on machine learning-based big data analytics for IoT-enabled smart healthcare system. Mobile Networks and Applications. 2021; 26:234-52.
[Crossref] [Google Scholar]
[2]Zhan K. Sports and health big data system based on 5G network and internet of things system. Microprocessors and Microsystems. 2021; 80:103363.
[Crossref] [Google Scholar]
[3]Aceto G, Persico V, Pescapé A. Industry 4.0 and health: internet of things, big data, and cloud computing for healthcare 4.0. Journal of Industrial Information Integration. 2020; 18:100129.
[Crossref] [Google Scholar]
[4]Karthik SA, Hemalatha R, Aruna R, Deivakani M, Reddy RV, Boopathi S. Study on healthcare security system-integrated internet of things (IoT). In perspectives and considerations on the evolution of smart systems 2023 (pp. 342-62). IGI Global.
[Crossref] [Google Scholar]
[5]Sarosh P, Parah SA, Bhat GM, Muhammad K. A security management framework for big data in smart healthcare. Big Data Research. 2021; 25:100225.
[Crossref] [Google Scholar]
[6]Lv Z, Qiao L. Analysis of healthcare big data. Future Generation Computer Systems. 2020; 109:103-10.
[Crossref] [Google Scholar]
[7]Selvaraj S, Sundaravaradhan S. Challenges and opportunities in IoT healthcare systems: a systematic review. SN Applied Sciences. 2020; 2(1):139.
[Crossref] [Google Scholar]
[8]Hariri RH, Fredericks EM, Bowers KM. Uncertainty in big data analytics: survey, opportunities, and challenges. Journal of Big Data. 2019; 6(1):1-6.
[Crossref] [Google Scholar]
[9]Bag S, Wood LC, Xu L, Dhamija P, Kayikci Y. Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources, Conservation and Recycling. 2020; 153:104559.
[Crossref] [Google Scholar]
[10]Dubey AK, Kushwaha GR, Shrivastava N. Heterogeneous data mining environment based on dam for mobile computing environments. In international conference on advances in information technology and mobile communication 2011 (pp. 144-9). Berlin, Heidelberg: Springer Berlin Heidelberg.
[Crossref] [Google Scholar]
[11]Duan Y, Edwards JS, Dwivedi YK. Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International Journal of Information Management. 2019; 48:63-71.
[Crossref] [Google Scholar]
[12]Kumari S, Patidar K, Kushwah R, Saxena G. A survey and analysis of big data management based on computational methodologies. ACCENTS Transactions on Image Processing and Computer Vision. 2020; 6(20):48-53.
[Crossref] [Google Scholar]
[13]Didas M. The barriers and prospects related to big data analytics implementation in public institutions: a systematic review analysis. International Journal of Advanced Computer Research. 2023; 13(64):29-54.
[Crossref]
[14]Hussin SK, Omar YM, Abdelmageid SM, Marie MI. Traditional machine learning and big data analytics in virtual screening: a comparative study. International Journal of Advanced Computer Research. 2020; 10(47):72-88.
[Crossref] [Google Scholar]
[15]Dubey AK, Kumar A, Agrawal R. An efficient ACO-PSO-based framework for data classification and preprocessing in big data. Evolutionary Intelligence. 2021; 14:909-22.
[Crossref] [Google Scholar]
[16]Fu W, Liu S, Srivastava G. Optimization of big data scheduling in social networks. Entropy. 2019; 21(9):902.
[Crossref] [Google Scholar]
[17]Olivera P, Danese S, Jay N, Natoli G, Peyrin-Biroulet L. Big data in IBD: a look into the future. Nature Reviews Gastroenterology & Hepatology. 2019; 16(5):312-21.
[Crossref] [Google Scholar]
[18]Sestino A, Prete MI, Piper L, Guido G. Internet of things and big data as enablers for business digitalization strategies. Technovation. 2020; 98:102173.
[Crossref] [Google Scholar]
[19]Qi CC. Big data management in the mining industry. International Journal of Minerals, Metallurgy and Materials. 2020; 27:131-9.
[Crossref] [Google Scholar]
[20]Bragazzi NL, Dai H, Damiani G, Behzadifar M, Martini M, Wu J. How big data and artificial intelligence can help better manage the COVID-19 pandemic. International Journal of Environmental Research and Public Health. 2020; 17(9):3176.
[Crossref] [Google Scholar]
[21]Hasan MM, Popp J, Oláh J. Current landscape and influence of big data on finance. Journal of Big Data. 2020; 7(1):1-7.
[Crossref] [Google Scholar]
[22]Baig MI, Shuib L, Yadegaridehkordi E. Big data in education: a state of the art, limitations, and future research directions. International Journal of Educational Technology in Higher Education. 2020; 17(1):1-23.
[Crossref] [Google Scholar]
[23]Agrawal R, Prabakaran S. Big data in digital healthcare: lessons learnt and recommendations for general practice. Heredity. 2020; 124(4):525-34.
[Crossref] [Google Scholar]
[24]León A, Pastor O. Enhancing precision medicine: a big data-driven approach for the management of genomic data. Big Data Research. 2021; 26:100253.
[Crossref] [Google Scholar]
[25]Nilashi M, Abumalloh RA, Almulihi A, Alrizq M, Alghamdi A, Ismail MY, et al. Big social data analysis for impact of food quality on travelers’ satisfaction in eco-friendly hotels. ICT Express. 2021.
[Crossref] [Google Scholar]
[26]Nikolov N, Dessalk YD, Khan AQ, Soylu A, Matskin M, Payberah AH, et al. Conceptualization and scalable execution of big data workflows using domain-specific languages and software containers. Internet of Things. 2021; 16:100440.
[Crossref] [Google Scholar]
[27]Arfanuzzaman M. Harnessing artificial intelligence and big data for SDGs and prosperous urban future in South Asia. Environmental and Sustainability Indicators. 2021; 11:100127.
[Crossref] [Google Scholar]
[28]Rohini P, Tripathi S, Preeti CM, Renuka A, Gonzales JL, Gangodkar D. A study on the adoption of wireless communication in big data analytics using neural networks and deep learning. In 2nd international conference on advance computing and innovative technologies in engineering 2022 (pp. 1071-6). IEEE.
[Crossref] [Google Scholar]
[29]Lutfi A, Alrawad M, Alsyouf A, Almaiah MA, Al-Khasawneh A, Al-Khasawneh AL, et al. Drivers and impact of big data analytic adoption in the retail industry: a quantitative investigation applying structural equation modeling. Journal of Retailing and Consumer Services. 2023; 70:103129.
[Crossref] [Google Scholar]
[30]Safa M, Pandian A, Gururaj HL, Ravi V, Krichen M. Real time health care big data analytics model for improved QoS in cardiac disease prediction with IoT devices. Health and Technology. 2023; 13(3):473-83.
[Google Scholar]