FoodBroker-Generating synthetic datasets for Graph-Based business analytics

Abstract

We present FoodBroker, a new data generator for benchmarking graph-based business intelligence systems and approaches. It covers two realistic business processes and their involved master and transactional data objects. The interactions are correlated in controlled ways to enable non-uniform distributions for data and relationships. For benchmarking data integration, the generated data is stored in two interrelated databases. The dataset can be arbitrarily scaled and allows comprehensive graph- and pattern-based analysis.