Analytics for Smart Keys application and User interface of streaming data

Big data has been a challenge for organizations and technology professionals because conventional software applications have struggled in the maintenance and analysis of big data. These software applications did not consider the immense growth of user generated data and struggled to keep up with the pace of the technology. It necessitated developing new applications that focused on the principles of artificial intelligence and data mining such that a heuristic search could provide meaningful results for big data. Smart keys applications and user interface of data streaming are two examples where it is crucial to manage big data for gaining competitive advantage in the contemporary context. This study analyses different aspects of big data in the context of analytics for smart keys application and user interface of streaming data. The study is based on the collection and analysis of secondary data. Data was collected from peer-reviewed journal articles, books, technology magazines, and other authenticated sources. The findings of the study indicated significant benefits of using big data analytics in smart keys applications and user streaming for big data. These applications are the best candidates for applying the concepts of big data analytics and organizations can gain a competitive advantage from the implementation.

Content

Author and article information

Journal

Journal ID (doi): 10.54878/EJBESS

Title: Emirati Journal of Business, Economics and Social Studies

Abbreviated Title: EJBESS

Publisher: Emirates Scholar

Publication date (Electronic): 15 November 2022

Volume: 1

Issue: 2

Pages: 110-123

Affiliations

[1 ]Emirates Scholar Research Center, United Arab Erimates

Author notes

Correspondence: Firas Habbal ( dr.firas@ 123456geminos.ae )

Article

DOI: 10.54878/EJBESS.209

SO-VID: 7c98b1c9-2b46-4b63-b2cb-7ef4ef663e19

License:

This is an open access article published by Emirates Scholar and distributed under the Creative Commons Attribution License 4.0 (CC BY).

History

Page count

Pages: 25

ScienceOpen disciplines: Economic theory,Management,Social & Behavioral Sciences,Business & Corporate economics,Economics

Keywords: Data Streaming, Big Data, Data Mining, Data Analytics, Smart Keys

References

J. Anuradha (2015) A brief introduction on Big data 5Vs characteristics and Hadoop Technology. Procedia computer science 48, 319–324
D. Blazquez , J. Domenech (2017) Big Data sources and methods for social and economic analyses. Technological Forecasting and Social Change.
E.T. Bradlow,x M. Gangwar, P. Kopalle, S. Voleti 2017 The role of big data and predictive analytics in retailing . Journal of Retailin 93(1), 79–95
M. Brinch, J. Stentoft, J.K. Jensen 2017 Big data and its applications in supply chain management: Findings from a Delphi stud. In Proceedings of the 50th Hawaii International Conference on System Sciences 93(1), 79–95
P. Chen,C. Zhang 2014 October 2017 Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Jounral of Information Science 275, 314–347 [Cross Ref]
E.S. Gartner 2017 10 Critical Tech Trends for the Next Five Years. Gartner Symposium IT Expo 275, 314–347 [Cross Ref]
E.S. Gartner 2017 Top 10 Strategic Technology Trends for 2013. Gartner Symposium IT Expo 275, 314–347 [Cross Ref]
K. Fang,Y. Jiang,M. Song 2016 Customer profitability forecasting using Big Data analytics: A case study of the insurance industry.. Computers and Industrial Engineering 101, 554–564
A. Gandomi,222M. Haider 2015 Beyond the hype: Big data concepts, methods, and analytics.. International Journal of Information Management, 35(2), 137–144
F. Habbal 2018 Big data: balancing between risks and opportunities–UAE perspective. International Journal of Economics and Business Research 15(4), 453–462
F. Habbal 2018 The smartphone technology acceptance among Emirati senior adults.. International Journal of Applied Engineering Research 12(20), 10114–10120
A.B. Hernández , M.S. Perez , S. Gupta , V. Muntés-Mulero 2017 Using machine learning to optimize parallelism in big data applications. Future Generation Computer Systems.
H.V. Jagadish,J. Gehrke,A. Labrinidis,Y. Papakonstantinou,J.M. Patel,R. Ramakrishnanel,C. Shahabi 2014 Big data and its technical challenges. Communications of the ACM 57(7), 86–94
A. Oussous,F.Z. Benjelloun,A.A Lahcen,S. Belfkih 2017 Big Data Technologies: A Survey. Journal of King Saud University-Computer and Information Sciences.
M.I. Pramanik,R.Y. Lau,H. Demirkan,M.A.K Azad 2017 Smart health: Big data enabled health paradigm within smart cities. Expert Systems with Applications 87, 373–383
C. Ranger,R. Raghuraman ,A. Penmetsa,G. Bradski ,C. Kozyrakis 2007 Evaluating MapReduce for multi-core and multiprocessor systems. Proceedings of the 13th IEEE International Symposium on High Performance Computer Architecture (HPCA '07) 13–14
J. Rajaraman , J. Ullman 2011 Mining of Massive Datasets . Cambridge University Press
S. Sonka 2014 Big data and the ag sector: More than lots of number. International Food and Agribusiness Management Review 17(1), 1–20
C. Tu , X. He, Z. Shuai, F. Jiang 2017 Big data issues in smart grid–A review.. Renewable and Sustainable Energy Reviews 79, 1099–1107
A.K. Zharova , V.M. Elin 2017 The use of Big Data: A Russian perspective of personal data security. Computer Law and Security Review. 79, 1099–1107

Comments

Comment on this article

[1] J. Anuradha (2015) A brief introduction on Big data 5Vs characteristics and Hadoop Technology. Procedia computer science 48, 319–324

[2] D. Blazquez , J. Domenech (2017) Big Data sources and methods for social and economic analyses. Technological Forecasting and Social Change.

[3] E.T. Bradlow,x M. Gangwar, P. Kopalle, S. Voleti 2017 The role of big data and predictive analytics in retailing . Journal of Retailin 93(1), 79–95

[4] M. Brinch, J. Stentoft, J.K. Jensen 2017 Big data and its applications in supply chain management: Findings from a Delphi stud. In Proceedings of the 50th Hawaii International Conference on System Sciences 93(1), 79–95

[5] P. Chen,C. Zhang 2014 October 2017 Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Jounral of Information Science 275, 314–347 [Cross Ref]

[6] E.S. Gartner 2017 10 Critical Tech Trends for the Next Five Years. Gartner Symposium IT Expo 275, 314–347 [Cross Ref]

[7] E.S. Gartner 2017 Top 10 Strategic Technology Trends for 2013. Gartner Symposium IT Expo 275, 314–347 [Cross Ref]

[8] K. Fang,Y. Jiang,M. Song 2016 Customer profitability forecasting using Big Data analytics: A case study of the insurance industry.. Computers and Industrial Engineering 101, 554–564

[9] A. Gandomi,222M. Haider 2015 Beyond the hype: Big data concepts, methods, and analytics.. International Journal of Information Management, 35(2), 137–144

[10] F. Habbal 2018 Big data: balancing between risks and opportunities–UAE perspective. International Journal of Economics and Business Research 15(4), 453–462

[11] F. Habbal 2018 The smartphone technology acceptance among Emirati senior adults.. International Journal of Applied Engineering Research 12(20), 10114–10120

[12] A.B. Hernández , M.S. Perez , S. Gupta , V. Muntés-Mulero 2017 Using machine learning to optimize parallelism in big data applications. Future Generation Computer Systems.

[13] H.V. Jagadish,J. Gehrke,A. Labrinidis,Y. Papakonstantinou,J.M. Patel,R. Ramakrishnanel,C. Shahabi 2014 Big data and its technical challenges. Communications of the ACM 57(7), 86–94

[14] A. Oussous,F.Z. Benjelloun,A.A Lahcen,S. Belfkih 2017 Big Data Technologies: A Survey. Journal of King Saud University-Computer and Information Sciences.

[15] M.I. Pramanik,R.Y. Lau,H. Demirkan,M.A.K Azad 2017 Smart health: Big data enabled health paradigm within smart cities. Expert Systems with Applications 87, 373–383

[16] C. Ranger,R. Raghuraman ,A. Penmetsa,G. Bradski ,C. Kozyrakis 2007 Evaluating MapReduce for multi-core and multiprocessor systems. Proceedings of the 13th IEEE International Symposium on High Performance Computer Architecture (HPCA '07) 13–14

[17] J. Rajaraman , J. Ullman 2011 Mining of Massive Datasets . Cambridge University Press

[18] S. Sonka 2014 Big data and the ag sector: More than lots of number. International Food and Agribusiness Management Review 17(1), 1–20

[19] C. Tu , X. He, Z. Shuai, F. Jiang 2017 Big data issues in smart grid–A review.. Renewable and Sustainable Energy Reviews 79, 1099–1107

[20] A.K. Zharova , V.M. Elin 2017 The use of Big Data: A Russian perspective of personal data security. Computer Law and Security Review. 79, 1099–1107