Online aggregation with tight error bounds in dynamic environments
OLAP is a category of database technology that allows analysts to gain insight into the aggregation of data by enabling them to gain access to a variety of different views of the information contained in a database. It is very important to provide analysts with guaranteed error bounds for approximate results to aggregation queries in enterprise applications such as decision support systems. We propose a general method of providing tight error bounds for approximate results to OLAP range-sum queries. We perform an extensive experiment on diverse data sets and examine the effectiveness of the proposed method for various data cube dimensions and query sizes.
online aggregation olap database decision support information system approximate query answering