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Capstone Project: Inadequate Data Storage Architectures
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Overview of the project topic
Lack of data storage architectures to handle a variety of applications has remained to be one of the problems IT professionals are facing in the modern world. There is a need to have efficient, scalable, and flexible data storage. Even though cloud computing has provided much-needed virtual storage, the IT community is still researching technology that will provide flexibility beyond cost and space in cloud storage options to improve IT infrastructure. Cloud architecture should provide long-term archival as opposed to short-term archival solutions to improve efficacy in the management of IT infrastructure (Ghani, 2020).
Description of the problem
Today’s IT ecosystem is faced with an increased amount of data that is generated by IoT devices. The biggest problem lies in how to effectively utilize the collected data for any meaningful use. “Data requires a place to rest, the same way objects need a shelf or container; data must occupy space” (Mehta, 2019). To store huge volumes of data, enterprises will require high-tech data centers that will require physical space in the office building. Setting up an in-house data center is a costly adventure that will also need experienced IT professionals to manage.
Solution
The ultimate solution to data storage problems lies in investing in cloud storage architecture. The enterprises must carefully examine whether they will set up an in-house data center or will outsource it from cloud vendors. Managing an in-house data center is quite expensive because there are the initial money required to set it up, labor and maintenance costs involved. Outsourcing cloud services seems to be the best solution because the organization will be freed from maintenance work hence the IT team can concentrate on other tasks (Villalobos, 2020). In addition, cloud vendors can help to solve scalability problems as they can allocate more storage space as needs demand.
References
Mehta, S., Kothuri, P., & Garcia, D. L. (2019). A big data architecture for log data storage and analysis. An Integrated Intelligent Computing, Communication and Security (pp. 201-209). Springer, Singapore.
Villalobos, K., Ramírez-Durán, V. J., Diez, B., Blanco, J. M., Goñi, A., & Illarramendi, A. (2020). A three level hierarchical architecture for an efficient storage of industry 4.0 data. Computers in Industry, 121, 103257.
Ghani, A., Badshah, A., Jan, S., Alshdadi, A. A., & Daud, A. (2020). Issues and challenges in cloud storage architecture: a survey. arXiv preprint arXiv:2004.06809.
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