Discuss about the Cloud Based Solution Of My Health Record Project.
The project on My Health Record supported by Commonwealth Government is a valuable project that records information of patients, doctors, healthcare providers and hospitals. This project is useful in healthcare industry and driving the performance and facility towards the patients and people related to healthcare (Mendelson & Wolf, 2017). The project is now considering adopting cloud based solutions due to facilities of cloud based solutions like data security. Hence, the purpose of this project is to analyze the cloud based solution through different aspects to meet the requirements of My Health Record project.
The structure of this report is as follows. The vendor solution including different types of vendors, review of cloud based solutions and SDLC approach towards cloud based solution.
The three vendors that are going to be described in the below paragraphs are Microsoft, Amazon and IBM that provide cloud based solutions. These three vendors provide systems to meet the requirement for My Health Record system in terms of data security, availability, seamless integration and others (Shawish & Salama, 2014). The below paragraphs will discuss the features of each vendor that will be suitable for the Information System.
The first vendor solution is Microsoft Azure which is widely used and it is the top player in the market and provides various beneficial features suitable for My Health Record (Pohekari, Patel & Shrivastava, 2017). The features are as follows and why it is suitable for My Health Record.
The second vendor solution is Amazon Web Services which is a highly reliable and scalable platform for My Health Record. The features are as follows.
The third vendor solution is IBM cloud is an appealing platform that provides seamless migration and methods to identify value in unstructured data suitable for My Health Record. The features are as follows.
The strengths and weaknesses of cloud based solutions, discussed in the above paragraph, are given in the following paragraphs by considering its deployment in My Health Record.
Microsoft Azure
Strengths
Weaknesses
Amazon Web Services
Strengths
Weaknesses
IBM Cloud
Strengths
Weaknesses
The SDLC approach to the project is discussed in this project using Predictive SDLC and Adaptive SDLC. The pros and cons of Predictive SDLC and adaptive SDLC are given below and recommendation of which SDLC approach for the project is suitable and why.
Pros
Cons
Pros
Cons
The recommended SDLC approach for the project is adaptive approach as this approach will be helpful to accommodate addition of various applications and terms in the project development (Noureen, Amjad & Azam, 2016). The addition of various users, doctors and others are accommodated through this approach. The policy requirements can also be applied for system benefits and this approach will easily accommodate these requirements. The flexibility and adjusting feature of this approach makes it suitable for the project.
Conclusion
Therefore, this report concludes that the vendors for the cloud based solutions discussed in this report are the suitable vendors for My Health Record project. The report briefly describes each of the vendors with suitability for the project and cloud based solutions brief description. The cloud based solution description with its benefits and limitation are described thoroughly. The SDLC approach shows that adaptive SDLC approach is suitable for the project due to its benefits of providing accommodation for adding requirements in any phase of project development. Hence, the report shows the brief analysis of cloud based solutions and its aspects.
References
Alharthi, A., Yahya, F., Walters, R. J., & Wills, G. (2015). An overview of cloud services adoption challenges in higher education institutions.
Jararweh, Y., Al-Ayyoub, M., Benkhelifa, E., Vouk, M., & Rindos, A. (2016). Software defined cloud: Survey, system and evaluation. Future Generation Computer Systems, 58, 56-74.
Kirmani, M. (2017). Agile methods for mobile application development: A comparative analysis. International Journal of Advanced Research in Computer Science, 8(5).
Malik, V., Sangwan, S., Saini, A., Ghalan, M., & Sangwan, N. (2017). Management of Various Risks over Years in SDLC. International Journal of Advanced Research in Computer Science, 8(5).
Matharu, G. S., Mishra, A., Singh, H., & Upadhyay, P. (2015). Empirical study of agile software development methodologies: A comparative analysis. ACM SIGSOFT Software Engineering Notes, 40(1), 1-6.
Mendelson, D., & Wolf, G. (2017). Health Privacy and Confidentiality.
Narula, S., & Jain, A. (2015, February). Cloud computing security: Amazon web service. In Advanced Computing & Communication Technologies (ACCT), 2015 Fifth International Conference on (pp. 501-505). IEEE.
Newcombe, C., Rath, T., Zhang, F., Munteanu, B., Brooker, M., & Deardeuff, M. (2015). How Amazon web services uses formal methods. Communications of the ACM, 58(4), 66-73.
Noureen, A., Amjad, A., & Azam, F. (2016). Model Driven Architecture-Issues, Challenges and Future Directions. JSW, 11(9), 924-933.
Philip, J., & Bharadi, V. A. (2016). Signature Verification SaaS Implementation on Microsoft Azure Cloud. Procedia Computer Science, 79, 410-418.
Pohekari, R., Patel, V., & Shrivastava, A. (2017). CYBER ATTACK DETECTION AND CLASSIFICATION USING MACHINE LEARNING TECHNIQUE USING MICROSOFT AZURE CLOUD.
Shawish, A., & Salama, M. (2014). Cloud computing: paradigms and technologies. In Inter-cooperative collective intelligence: Techniques and applications (pp. 39-67). Springer, Berlin, Heidelberg.
Shrivastava, A., Sondhi, J., & Kumar, B. (2017). MACHINE LEARNING TECHNIQUE FOR PRODUCT CLASSIFICATION IN E-COMMERCE DATA USING MICROSOFT AZURE CLOUD.
Van, V. N., Long, N. Q., Nguyen, G. N., & Le, D. N. (2016). A performance analysis of openstack open-source solution for iaas cloud computing. In Proceedings of the Second International Conference on Computer and Communication Technologies (pp. 141-150). Springer, New Delhi.
Varia, J., & Mathew, S. (2014). Overview of amazon web services. Amazon Web Services.
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