Skip to main content

2024 | OriginalPaper | Buchkapitel

10. Real-World Big Data Analytics Case Studies

verfasst von : Ümit Demirbaga, Gagangeet Singh Aujla, Anish Jindal, Oğuzhan Kalyon

Erschienen in: Big Data Analytics

Verlag: Springer Nature Switzerland

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This chapter unfolds a panoramic view across diverse sectors, unveiling the transformative impact of big data analytics on real-world challenges. The exploration commences in the government sector, where data-driven governance enhances public services, enables predictive analytics for smart city planning, fortifies security and surveillance, and even extends to election forecasting and voter analytics. Transitioning to the healthcare industry, the chapter delves into the revolutionary role of big data analytics in tailoring treatments through precision medicine and predicting and preventing disease outbreaks. The entertainment industry takes centre stage, showcasing applications such as content personalization, recommendation systems, box office predictions, revenue optimization, and audience engagement through social media analytics. The banking sector comes to life with risk assessment, credit scoring, customer relationship management, personalization, fraud detection, security, and strategic decision-making. The retail industry follows suit, emphasising inventory management, demand forecasting, customer segmentation, personalization, supply chain optimization, and in-store analytics. The chapter finally highlights the energy and utilities sector by illuminating applications in grid management, smart grids, predictive maintenance, asset optimization, energy generation, renewable integration, energy efficiency, demand response, and environmental sustainability.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat J.C. Bertot, H. Choi, Big data and e-government: issues, policies, and recommendations,” in Proceedings of the 14th Annual International Conference on Digital Government Research (2013), pp. 1–10 J.C. Bertot, H. Choi, Big data and e-government: issues, policies, and recommendations,” in Proceedings of the 14th Annual International Conference on Digital Government Research (2013), pp. 1–10
2.
Zurück zum Zitat E. Gummesson, Case theory in business and management: Reinventing case study research, in Case Theory in Business and Management (2017), pp. 1–368 E. Gummesson, Case theory in business and management: Reinventing case study research, in Case Theory in Business and Management (2017), pp. 1–368
3.
Zurück zum Zitat A. Jindal, A. Dua, N. Kumar, A.V. Vasilakos, J.J. Rodrigues, An efficient fuzzy rule-based big data analytics scheme for providing healthcare-as-a-service, in 2017 IEEE International Conference on Communications (ICC) (2017), pp. 1–6 A. Jindal, A. Dua, N. Kumar, A.V. Vasilakos, J.J. Rodrigues, An efficient fuzzy rule-based big data analytics scheme for providing healthcare-as-a-service, in 2017 IEEE International Conference on Communications (ICC) (2017), pp. 1–6
4.
Zurück zum Zitat J.C. Bertot, E. Estevez, T. Janowski, Digital public service innovation: Framework proposal, in Proceedings of the 9th International Conference on Theory and Practice of Electronic Governance (2016), pp. 113–122 J.C. Bertot, E. Estevez, T. Janowski, Digital public service innovation: Framework proposal, in Proceedings of the 9th International Conference on Theory and Practice of Electronic Governance (2016), pp. 113–122
5.
Zurück zum Zitat S. Xu, Y. Qian, R.Q. Hu, Data-driven network intelligence for anomaly detection. IEEE Network 33(3), 88–95 (2019)CrossRef S. Xu, Y. Qian, R.Q. Hu, Data-driven network intelligence for anomaly detection. IEEE Network 33(3), 88–95 (2019)CrossRef
6.
Zurück zum Zitat K. Soomro, M.N.M. Bhutta, Z. Khan, M.A. Tahir, Smart city big data analytics: An advanced review. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 9(5), e1319 (2019) K. Soomro, M.N.M. Bhutta, Z. Khan, M.A. Tahir, Smart city big data analytics: An advanced review. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 9(5), e1319 (2019)
7.
Zurück zum Zitat B. Wilson, A. Chakraborty, The environmental impacts of sprawl: Emergent themes from the past decade of planning research. Sustainability 5(8), 3302–3327 (2013)CrossRef B. Wilson, A. Chakraborty, The environmental impacts of sprawl: Emergent themes from the past decade of planning research. Sustainability 5(8), 3302–3327 (2013)CrossRef
8.
Zurück zum Zitat Y. Kaluarachchi, Potential advantages in combining smart and green infrastructure over silo approaches for future cities. Front. Eng. Manage. 8, 98–108 (2021)CrossRef Y. Kaluarachchi, Potential advantages in combining smart and green infrastructure over silo approaches for future cities. Front. Eng. Manage. 8, 98–108 (2021)CrossRef
9.
Zurück zum Zitat L. Quijano-Sánchez, I. Cantador, M.E. Cortés-Cediel, O. Gil, Recommender systems for smart cities. Inf. Syst. 92, 101545 (2020)CrossRef L. Quijano-Sánchez, I. Cantador, M.E. Cortés-Cediel, O. Gil, Recommender systems for smart cities. Inf. Syst. 92, 101545 (2020)CrossRef
10.
Zurück zum Zitat Y. El-Ghalayini, H. Al-Kandari, Big data regulatory legislation: Security, privacy and smart city governance. JL Pol’y Global. 95, 19 (2020) Y. El-Ghalayini, H. Al-Kandari, Big data regulatory legislation: Security, privacy and smart city governance. JL Pol’y Global. 95, 19 (2020)
11.
Zurück zum Zitat M. Mahbub, Progressive researches on iot security: An exhaustive analysis from the perspective of protocols, vulnerabilities, and preemptive architectonics. J. Network Comput. Appl. 168, 102761 (2020)CrossRef M. Mahbub, Progressive researches on iot security: An exhaustive analysis from the perspective of protocols, vulnerabilities, and preemptive architectonics. J. Network Comput. Appl. 168, 102761 (2020)CrossRef
12.
Zurück zum Zitat G.C. Oatley, Themes in data mining, big data, and crime analytics. Wiley Interdiscip. Rev. Data Min. Knowl. Disc. 12(2), e1432 (2022) G.C. Oatley, Themes in data mining, big data, and crime analytics. Wiley Interdiscip. Rev. Data Min. Knowl. Disc. 12(2), e1432 (2022)
13.
Zurück zum Zitat W. Chen, A. Quan-Haase, Big data ethics and politics: Toward new understandings. Soc. Sci. Comput. Rev. 38(1), 3–9 (2020)CrossRef W. Chen, A. Quan-Haase, Big data ethics and politics: Toward new understandings. Soc. Sci. Comput. Rev. 38(1), 3–9 (2020)CrossRef
14.
Zurück zum Zitat E.F. Judge, M. Pal, Voter Privacy and Big-data Elections, vol. 58 (Osgoode Hall LJ, 2021), p. 1 E.F. Judge, M. Pal, Voter Privacy and Big-data Elections, vol. 58 (Osgoode Hall LJ, 2021), p. 1
15.
Zurück zum Zitat F. Gilardi, Digital Technology, Politics, and Policy-Making. (Cambridge University Press, 2022) F. Gilardi, Digital Technology, Politics, and Policy-Making. (Cambridge University Press, 2022)
16.
Zurück zum Zitat N. Mehta, A. Pandit, M. Kulkarni, Elements of Healthcare Big data Analytics. Big Data Analytics in Healthcare (2020), pp. 23–43 N. Mehta, A. Pandit, M. Kulkarni, Elements of Healthcare Big data Analytics. Big Data Analytics in Healthcare (2020), pp. 23–43
17.
Zurück zum Zitat S. Huang, J. Yang, S. Fong, Q. Zhao, Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges. Cancer Lett. 471, 61–71 (2020)CrossRef S. Huang, J. Yang, S. Fong, Q. Zhao, Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges. Cancer Lett. 471, 61–71 (2020)CrossRef
18.
Zurück zum Zitat S. Khanra, A. Dhir, A.N. Islam, M. Mäntymäki, Big data analytics in healthcare: a systematic literature review. Enterpr. Inf. Syst. 14(7), 878–912 (2020)CrossRef S. Khanra, A. Dhir, A.N. Islam, M. Mäntymäki, Big data analytics in healthcare: a systematic literature review. Enterpr. Inf. Syst. 14(7), 878–912 (2020)CrossRef
19.
Zurück zum Zitat T. Hulsen, S.S. Jamuar, A.R. Moody, J.H. Karnes, O. Varga, S. Hedensted, R. Spreafico, D.A. Hafler, E.F. McKinney, From big data to precision medicine. Front. Med. 6, 34 (2019)CrossRef T. Hulsen, S.S. Jamuar, A.R. Moody, J.H. Karnes, O. Varga, S. Hedensted, R. Spreafico, D.A. Hafler, E.F. McKinney, From big data to precision medicine. Front. Med. 6, 34 (2019)CrossRef
20.
Zurück zum Zitat A. O’Driscoll, J. Daugelaite, R.D. Sleator, Big data, hadoop and cloud computing in genomics. J. Biomed. Inf. 46(5), 774–781 (2013)CrossRef A. O’Driscoll, J. Daugelaite, R.D. Sleator, Big data, hadoop and cloud computing in genomics. J. Biomed. Inf. 46(5), 774–781 (2013)CrossRef
21.
Zurück zum Zitat M. Herrero-Zazo, T. Fitzgerald, V. Taylor, H. Street, A.N. Chaudhry, J.R. Bradley, E. Birney, V.L. Keevil, Using machine learning to model older adult inpatient trajectories from electronic health records data. Iscience 26(1) (2023) M. Herrero-Zazo, T. Fitzgerald, V. Taylor, H. Street, A.N. Chaudhry, J.R. Bradley, E. Birney, V.L. Keevil, Using machine learning to model older adult inpatient trajectories from electronic health records data. Iscience 26(1) (2023)
22.
Zurück zum Zitat K.Y. Ngiam, W. Khor, Big data and machine learning algorithms for health-care delivery. Lancet Oncol. 20(5), e262–e273 (2019)CrossRef K.Y. Ngiam, W. Khor, Big data and machine learning algorithms for health-care delivery. Lancet Oncol. 20(5), e262–e273 (2019)CrossRef
23.
Zurück zum Zitat M.I. Razzak, M. Imran, G. Xu, Big data analytics for preventive medicine. Neural Comput. Appl. 32, 4417–4451 (2020)CrossRef M.I. Razzak, M. Imran, G. Xu, Big data analytics for preventive medicine. Neural Comput. Appl. 32, 4417–4451 (2020)CrossRef
24.
Zurück zum Zitat A.N. Desai, M.U. Kraemer, S. Bhatia, A. Cori, P. Nouvellet, M. Herringer, E.L. Cohn, M. Carrion, J.S. Brownstein, L.C. Madoff et al., Real-time epidemic forecasting: challenges and opportunities. Health Sec. 17(4), 268–275 (2019)CrossRef A.N. Desai, M.U. Kraemer, S. Bhatia, A. Cori, P. Nouvellet, M. Herringer, E.L. Cohn, M. Carrion, J.S. Brownstein, L.C. Madoff et al., Real-time epidemic forecasting: challenges and opportunities. Health Sec. 17(4), 268–275 (2019)CrossRef
25.
Zurück zum Zitat H. Lippell, Big data in the media and entertainment sectors, in New Horizons for a Data-Driven Economy: A Roadmap for Usage and Exploitation of Big Data in Europe (2016), pp. 245–259 H. Lippell, Big data in the media and entertainment sectors, in New Horizons for a Data-Driven Economy: A Roadmap for Usage and Exploitation of Big Data in Europe (2016), pp. 245–259
26.
Zurück zum Zitat U. Srivastava, S. Gopalkrishnan, Impact of big data analytics on banking sector: Learning for indian banks. Procedia Comput. Sci. 50, 643–652 (2015)CrossRef U. Srivastava, S. Gopalkrishnan, Impact of big data analytics on banking sector: Learning for indian banks. Procedia Comput. Sci. 50, 643–652 (2015)CrossRef
27.
Zurück zum Zitat M.G. Dekimpe, Retailing and retailing research in the age of big data analytics. Int. J. Res. Market. 37(1), 3–14 (2020)CrossRef M.G. Dekimpe, Retailing and retailing research in the age of big data analytics. Int. J. Res. Market. 37(1), 3–14 (2020)CrossRef
28.
Zurück zum Zitat K. Zhou, C. Fu, S. Yang, Big data driven smart energy management: From big data to big insights. Renew. Sustain. Energy Rev. 56, 215–225 (2016)CrossRef K. Zhou, C. Fu, S. Yang, Big data driven smart energy management: From big data to big insights. Renew. Sustain. Energy Rev. 56, 215–225 (2016)CrossRef
29.
Zurück zum Zitat J.R. Owens, B. Femiano, J. Lentz, Hadoop Real World Solutions Cookbook. (Packt Publishing, 2013) J.R. Owens, B. Femiano, J. Lentz, Hadoop Real World Solutions Cookbook. (Packt Publishing, 2013)
30.
Zurück zum Zitat T. Dunning, E. Friedman, Real-World Hadoop. (O’Reilly Media, Inc., 2015) T. Dunning, E. Friedman, Real-World Hadoop. (O’Reilly Media, Inc., 2015)
31.
Zurück zum Zitat M. Grover, T. Malaska, J. Seidman, G. Shapira, Hadoop Application Architectures: Designing Real-world Big Data Applications. (O’Reilly Media, Inc., 2015) M. Grover, T. Malaska, J. Seidman, G. Shapira, Hadoop Application Architectures: Designing Real-world Big Data Applications. (O’Reilly Media, Inc., 2015)
Metadaten
Titel
Real-World Big Data Analytics Case Studies
verfasst von
Ümit Demirbaga
Gagangeet Singh Aujla
Anish Jindal
Oğuzhan Kalyon
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-55639-5_10

Premium Partner