Final Project: You will assemble your final report as follows:

Implementing Cloud Services in a Data Analytics Firm

The acceptance of cloud computing services is rapidly increasing data analytics firms search for method that they can use to exploit in relation to computing infrastructure without owning physical assets. Presently, firm are not investing in hardware, software, data centers, and support staff an undertaking that has allowed them to concentrate on their principal offerings. However, with opportunity comes risks and therefore data analytic firms must effectively mitigate possible liabilities and improve their processes decision-making. To this effect, this paper intends to evaluate best approaches that a data analytic firm can employ when using Cloud services.

Generally, cloud computing services (CCS) follow two models namely public cloud and private cloud. A public cloud is a computing infrastructure that has no usage restrictions in relation to region or geographical factors. It uses shared resources, and therefore it can be scaled up or down very quickly. Besides, it is very efficient since users only pay for what they use. Accordingly, data can be stored in one or several locations simultaneously. Nonetheless, a public cloud has major risks like its reliability, security, and compliance with regulations. On the other hand, a private cloud refers to a computing infrastructure operating from a localized region or geographical environment and with resources are strictly dedicated to a specific firm (Mahmood, 2013). Under this model, reliability and security are contractually agreed upon and a high degree of regulatory compliance is developed. However, it is expensive and it cannot be scaled up or down as fast as a public cloud.

Irrespective of the selected CCS model it is important to understand the type of data being stored by the host so that one can determine the risks involved. Most importantly, it is crucial to make sure that data protection and privacy policies are known, clear and under control. For instance, for a data analytic firm, it would be prudent to understand what will happen to the firm’s data once the agreement with the CCS provider is terminated. The rationale is that some providers will store data indefinitely and hence the firm should ensure that after the termination of the contract, all data is completely removed and expunged (Mahmood, 2013). Further, it is important to understand the firm’s obligations under the current contract to establish whether the firm’s data requires segregation in the event that it is stored in a CCS that may co-mingle storage.

Alternatively, to leverage the risks involved in using either the public or private cloud models, the firm can use the hybrid cloud model. This model is attractive because it helps cloud service customers to address their specific business needs, incur low cost and at the same time leverage the leading-edge functionality available under the public cloud model (Sarna, 2011). Conversely, by using private cloud it is able to manage its sensitive data and applications. Thus, for the current firm the deployment of the hybrid cloud model would be essential since it would help the firm to leverage a combination of public and private cloud deployments subject to its needs for available resources, speed of execution, need for data security and, and a range of other reasons.

Consequently, after selecting the model to use, the firm should determine the most effective method to design, develop, deploy and maintain the cloud applications. The strategy should be guided by the firm’s needs and capabilities. Typically, there are four options that the firm can consider:

· Internal development and deployment

· Autonomous cloud service development provider

· Cloud provider development and deployment

· Off-the-shelf subscription of a cloud application service

Choosing a methodology for implementing a cloud application varies depending on the size of the firm. Typically, the skills available at the current organization are only targeted towards supporting the firm’s current applications and therefore it would be sensible to consider contracting resources from a cloud service provider. It is also in the firm’s objective to reduce its expenses; besides the firm will enjoy the flexibility of re-assigning internal skills to the cloud deployment as well as accommodate the changeover to cloud internally (Mahmood, 2013). Finally, after the business case for cloud computing has been executed and both business drivers and projected return on investment have been determined, it is important to get the approval and disapproval from the management.

Presently, firms are using either or a combination of existing CCS models depending on its needs for execution speed, available resources, data security and protection, and centralized management to name a few. Thus, it will be important for the firm t first identify its needs before it selects the best model to use. In addition, it will be important to develop “cloud native” applications as well as the architectures and technologies that have advanced to support them. For example, the use of microservices, “server-less” computing, containers, and architecture are becoming common. Therefore, for this firm it will be necessary to consider these aspects of cloud computing when making a decision on which cloud services to adopt.

IMPLEMENTING CLOUD SERVICES IN A DATA ANALYTICS FIRM 5

References

Catlett, C. (2013). Cloud computing and big data. Amsterdam, Netherlands: IOS Press.

Mahmood, Z. (2013). Cloud Computing. Computer Communications And Networks. doi: 10.1007/978-1-4471-5107-4

Sarna, D. (2011). Implementing and developing cloud computing applications. Boca Raton, FL: CRC Press.