Big Data Analytics-A Brief Research Synthesis

This paper presents a brief research synthesis based on the author's experience from a number of big data analytic projects completed with privately owned companies spanning transportation, telecommunication and manufacturing industries. The projects have primarily been completed using records of the companies' transactions (sales, production orders, client calls etc.). The main idea is to give a synthesis of the challenges in completing big data analytic projects to support both strategic but especially operational decisions and present the potential pit falls in these projects. The main conclusions are: that big data analytics requires high quality data if one desires to develop complex explanatory and predictive models, that developing complex models is not a goal in itself, that responses between variables may be lagged in time and difficult to establish and that the challenge of the future is to create automated decision making systems exploiting the models created from big data analytics.