Specification-Based Data Reduction in Dimensional Data Warehouses

Data warehouses are often very large, with new data being appended regularly. The sheer size and complexity of such warehouses makes them hard to manage effectively and to query with the desired efficiency. Although disk prices drop continuously, this neither solves the complexity nor the performance problems. Also, some data becomes unreliable or irrelevant as time passes. Examples include exact addresses of graduated students and the URLs of web pages. However, much such data continues to be of interest at an aggregated level as it ages. This poster presents a powerful and easy-to-use technique [1] for aggregation-based data reduction that enables the gradual change of the data from being detailed to being increasingly aggregated. The technique enables huge storage gains while retaining the data that is essential to th