Abstract:

More and more data is collected from a variety of new sources such as sensors, smart devices, social media, crowd-sourcing, and (Linked) Open Data. Such data is large, fast, and often complex. There is a universal wish to perform multidimensional OLAP-style analytics on such data, i.e., to turn it into “Big Multidimensional Data”. The talk will look at (open) challenges and solutions in managing Big Multidimensional Data. This is a multi-stage journey from the initial data acquisition, over cleansing, transformation and modeling, to (distributed) storage, indexing, and query processing; further on to building (predictive) models over data, and ultimately performing prescriptive analytics that integrates analytics with optimization to suggest optimal actions. Case studies from application domains such as Smart Energy, Smart Transport, and Linked Open Data are used for illustration.