A Scheduling Strategy for OLAM Tasks and Its Application in a Financial BI System

This paper proposes a scheduling strategy which divides OLAM (online analytical mining) tasks into query tasks, mining tasks and updating tasks in order to improve the efficiency of BI (business intelligence) systems. OLAM mechanism is considered as the seamless integration of OLAP (online analytical processing) and data mining on data cubes, according to which the scheduling strategy focuses on. This paper emphasizes the interaction of OLAP, data mining and data cube updating, illustrates the details of the OLAM scheduling strategy and demonstrates its efficiency by performing it in a financial BI system.