In this project, we developed a platform that incorporates a set of data management and analytics tools to facilitate joining the independent works of the data scientists, addressing usability and performance issues. The goal of this project as such was twofold. First, the platform aimed to bridge the gap between data analytics: managing the data, analyzing it, and visualizing the analysis results. We accomplished this by streamlining those three phases to alleviate the burden from data scientists and to use parallel processing on shared-nothing architecture to enhance performance. Second, the platform aimed to provide standards and infrastructure to answer complex questions. This platform can be used to build several computational and data-intensive models. We also developed an application (built on top of the platform) that quickly answers complex questions that may involve many complex models.