Big data analytics has little to do with analytics

Abstract

As big data analytics is adapted across multitude of domains and applications there is a need for new platforms and architectures that support analytic solution engineering as a lean and iterative process. In this paper we discuss how different software development processes can be adapted to data analytic process engineering, incorporating service oriented architecture, scientific workflows, model driven engineering and semantic technology. Based on the experience obtained through ADAGE framework [1] and the findings of the survey on how semantic modeling is used for data analytic solution engineering [6], we propose two research directions - big data analytic development lifecycle and data analytic knowledge management for lean and flexible data analytic platforms.