Economy of scale is a key driver behind the Cloud based adoption of a business process. Typically, the management of business process variants focuses on design variants, which permit (ideally small) variations in design (and hence, functionality) for achieving the same (functional) goal, under different functional constraints (such as the compliance obligations that have to be met in different jurisdictions). Little attention has been paid to: (a) variations in process design driven by non-functional considerations (e.g., performance, reliability and cost of operation) and (b) variations in process provisioning in Cloud. This paper seeks to develop means for identifying the correlation between both design and provisioning alternatives and the QoS of business processes deployed in the Cloud. Additionally, we explore the role of the context in determining the performance of a process. We use a set of data mining techniques (specifically decision tree learning, support vector machine and the k-nearest neighbour technique) to mine insights about these correlations. Proposed approaches are evaluated using a synthetic dataset as well as a real dataset.