The Interactive Data Language (IDL) is a standard tool used by many researchers in observational fields. Present day Sun-Earth Connection missions like SOHO, or future missions, including the Solar Dynamics (SDO) almost exclusively analyze their data in IDL. However, the increasing amount of data produced by these missions, and the increasing complexity of image processing algorithms, requires higher computing power. Cluster computing is a cost-effective way to increase the speed of computation. Enhancing IDL to work on clusters gives scientists access to increased performance in a familiar programming environment. We propose to develop a tool suite that enables IDL to benefit from cluster systems. We demonstrated in Phase I the availability of all key technologies by developing prototype implementations. The main emphasis of the Phase II will be to enhance the interactivity of the tools and advance the suite to market-ready quality. Increased data analysis power enables e.g. near real-time data analysis for space-weather prediction or reduces the response time for analyzing data on demand, as desirable in virtual observatory environments. The wide spread of IDL allows scientists from other fields to benefit from the increased execution speed.