<![CDATA[Organizations need to understand the importance of resource allocation and traffic forecasting for cloud computing more than ever because of the increasing demand for online services, data storage and remote work, which makes it challenging to estimate traffic and distribute resources. In cloud computing, there is still opportunity for increasing the model's forecast accuracy. The more accurate the traffic flow, the better the resource allocation. Therefore, this study investigate the adequate data analytic frameworks for managing cloud computing resource allocation in the organisation, According to the findings, six technique were used just for prediction, while one was utilized solely for resource allocation. In this sense, cloud computing resource allocation and prediction may be achieved by combining several techniques.this paper contributes the review to identify adequate data analytic frameworks for managing cloud computing resource allocation.]]>
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