ABSTRACT
This entry demonstrates a big data analytics approach designed to support discovering and leveraging informative patterns in large-scale multidimensional temporal data of transactions. This type of data is abundant in many domains of human activity. The approach can be adjusted to specific application scenarios. It provides a few instances of societally and commercially beneficial use of the proposed approach. These examples leverage comprehensive screening of large databases for multiple aspects of change, which in turn may help explain existing events and carry forthcoming information.
