Cloud Computing Technologies and the Economic Impact of Digitalization


  • Gabriela Ignat
  • Lilia Sargu
  • Ioan Prigoreanu


cloud computing; Oracle; SaaS; integrated platforms; business intelligence


Nowadays, the use of the Internet and new technologies, for business and people, is part of everyday life. Thanks to the Internet, any information is available anywhere in the world at any time, and this was not available a few years ago. The term Cloud Computing describes a variety of concepts that involve a large number of computers connected through a network in real time, this being possible with the help of the Internet. Cloud computing is the most popular and widely used technology today.Big data, storage capacity and inadequate analysis are challenging many organizations today and require perfect data management techniques and analytical models to implement an integrated business intelligence solution.


Al-Aqrabi, H., Liu, L., Hill, R. and Antonopoulos, N. (2015). Cloud BI: Future of business intelligence in the Cloud. Journal of Computer and System Sciences, 81(1), pp.85-96.

Alsufyani, R. and Chang, V. (2015). Risk Analysis of Business Intelligence in Cloud Computing. 2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom).

Arora, R, PK Arora, H Kumar and M Pant (2020). Additive manufacturing enabled supplychain in combating COVID-19. Journal of Industrial Integration and Management, 5(4),495–505.

Bahl, S, M Javaid, AK Bagha, RP Singh, A Haleem, R Vaishya and R Suman (2020a).Biosensors applications in ¯ghting COVID-19 pandemic. Apollo Medicine, doi: 10.4103/am.am56 20.

Banda, M. and Ngassam, E. (2017). A data management and analytic model for business intelligence applications. 2017 IST-Africa Week Conference (IST-Africa).

Basilaia, G, M Dgebuadze, M Kantaria and G Chokhonelidze (2020). Replacing the classiclearning form at universities as an immediate response to the COVID-19 virus infection inGeorgia. International Journal for Research in Applied Science and Engineering Tech-nology, 8, 101–108.

Bauer, E. (2018). Cloud Automation and Economic Efficiency. IEEE Cloud Computing, 5(2), pp.26-32.

Bellini, P., Cenni, D. and Nesi, P. (2015). A Knowledge Base Driven Solution for Smart Cloud Management. 2015 IEEE 8th International Conference on Cloud Computing.

Chang, V., Kuo, Y. and Ramachandran, M. (2016). Cloud computing adoption framework: A security framework for business clouds. Future Generation Computer Systems, 57, pp.24-41.

Iyengar, KP, R Vaishya, S Bahl and A Vaish (2020b). Impact of the coronavirus pandemic onthe supply chain in healthcare. British Journal of Healthcare Management, 26(6), 1–4.

Jasmine, CA (2019). Impacts of Covid-19 on Company and E®orts to Support OrganizationAdaptable. Dr. David F. Rico, PMP, ACP, CSM,67–70.Cloud Computing in Solving Problems of COVID-19 Pandemic 217

Kim, Y. and Huh, E. (2017). Towards the Design of a System and a Workflow Model for Medical Big Data Processing in the Hybrid Cloud. 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech).

Larson, D. and Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), pp.700-710.

Liang, T. and Liu, Y. (2018). Research Landscape of Business Intelligence and Big Data analytics: A bibliometrics study. Expert Systems with Applications, 111, pp.2-10.

Sahmim, S. and Gharsellaoui, H. (2017). Privacy and Security in Internet-based Computing: Cloud Computing, Internet of Things, Cloud of Things: a review. Procedia Computer Science, 112, pp.1516-1522.

Singh, RP, M Javaid, R Kataria, M Tyagi, A Haleem and R Suman (2020c). Signicantapplications of virtual reality for COVID-19 pandemic. Diabetes & Metabolic Syndrome:Clinical Research & Reviews, 14(4), 661–664.

Stergiou, C., Psannis, K., Gupta, B. and Ishibashi, Y. (2018). Security, privacy & efficiency of sustainable Cloud Computing for Big Data & IoT. Sustainable Computing: Informatics and Systems, 19, pp.174-184.

Subramanian, N. and Jeyaraj, A. (2018). Recent security challenges in cloud computing. Computers & Electrical Engineering, 71, pp.28-42.

Wang, B. and Tang, J. (2016). The Analysis of Application of Cloud Computing in E- Commerce. 2016 International Conference on Information System and Artificial Intelligence (ISAI).

Wazurkar, P., Bhadoria, R. and Bajpai, D. (2017). Predictive analytics in data science for business intelligence solutions. 2017 7th International Conference on Communication Systems and Network Technologies (CSNT).

Xu, LD and L Duan (2019). Big data for cyber-physical systems in industry 4.0: A survey.Enterprise Information Systems, 13(2), 148–169.

Xu, LD, EL Xu and L Li (2018). Industry 4.0: State of the art and future trends. InternationalJournal of Production Research, 56(8), 2941–2962



*** us/help/2925359/microsoft-dynamics-crm-online-releases/



*** need-know-buy/