The most complex process is to collect huge amount of beneficial information from available data. But this can be made convenient by modelling a Data Analysis Workflow. To analyze the large data sets, Data Analysis Workflows may consume more time to execute completely. This situation is the same even when complex data mining Algorithms are used. Hence to make execution of Data Workflow Analysis more scalable for efficient systems, there is a need to make exploit the computing services of the cloud structures where in information is increasingly being saved. This Paper presents a method to design and implement a Data Mining Cloud Framework (DMCF), which integrates the Data Workflow Language and parallel runtime SaaS model. The main goal of DMCF is to simplify the development of data mining Algorithms keeping Real Data Mining Applications in mind.
