We have developed a workflow framework that simplifies the complexity in workflow management/execution for big
data analytics. The framework provides services for remote and parallel executions of the workflows submitted by the workflow composers, who might be data scientists and application developers as well as non-data mining experts, from any devices such as desktops, laptops, and mobiles. To achieve parallel multiple workflow executions, the submitted work- flows are efficiently scheduled to meet workflow execution requirements (e.g., deadlines), and tasks are substituted with the corresponding parallel tasks (e.g., written in MapReduce- equivalent programming not restricted to specific softwares). In particular, workflow/task scheduling, resource provisioning, and data staging are addressed by the framework.