This research group seeks to exploit the myriad promises conferred by big data. In the past, traditional descriptive analytics (or, detective analytics) could only equip organizations with fundamental operational observations, signaling deviations and raising alarms when necessary. Moving forward, organizations favor predictive analytics that can help forecast and predict potential relationships between variables and outcomes of concern, so that they can better chart their future and achieve their goals. In this way, analytics has proven useful in helping organizations know what they know and what they don’t. But the untamed potential of big data is even greater – as big data analytics promises to enlighten organizations regarding knowledge discovery, or help them understand what they do not even know they don’t know.

Big data has been characterized by the 4Vs, namely “volume” (i.e., data sets whose size is beyond the ability of conventional database software tools to capture, store, manage, and analyze), “variety” (i.e., comprising not only of structured data that is traditionally captured and managed by relational databases, but also of semi-structured or even unstructured data, which calls for new analytical techniques), “velocity” (i.e., extremely fast speed of data generation and the “real-time” speed with which data needs to be captured and analyzed in order to maximize its business value) and “veracity” (i.e., the uncertainty in data that normally results from data inaccuracy, inconsistency, and incompleteness since it comes from different platforms, in different forms, using different metrics). However, although big data analytics holds much promise, it is no silver bullet. Our research group works on overcoming the challenges of big data in manifold ways. We are working toward providing tangible and novel insights, and recommending strategic actions for organizations in their analytics efforts. Broadly, the three areas that we cover are: