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The context of data and process is critically important to the understanding of computational sciences. This context is referred to as provenance in distributed, grid and workflow computing and has implications like trust, reliability, verification, reproduction, etc. In this paper, we present various application scenarios of the provenance data and the implication of such data for the Cloud infrastructure. These applications includes, (i) to find patterns in the usage of Cloud resources which are based on resource types, instances types and user data, (ii) reusing existing resources which are populated by other users of the Cloud and (iii) providing an improved fault tracking system which can be further enhanced for the fault management. These are absolute advantages and the data can be further utilized for various other scenarios, e.g., trust and reliability in the Cloud. Mainly, we focus on the storage mechanism of provenance data and the usage of such data via query, visualization and the utilization of Cloud resources.