Parallel data processing, analysis and visualization using high scalability mechanisms

In this work we present conceptual and implementation model for scalable, distributed and balanced execution of large number of compute operations running on multiple processing units in the cloud. We provide system development methods for large scale processing with minimal time constraints and limitations in regard to increasing scale-out parallelism in the cloud. Implementation details regarding elastic adjustment to processing units are discussed in connection to required processing power needed in a cloud environment. Work provides filtering approaches for useful data in the described problem domain. We present options for advanced data filtering in multiple stages, which correlate with needed analyses requirements. At the end of this work we present ways of visualization of advanced analysis of gathered data in a form of intuitive and interactive UI components, graphs, word clouds and other user acceptable views