Title: Supporting Aggregation in Data Warehousing Considering User-Defined Temporal Granularities

Year of Publication: Sep - 2015
Page Numbers: 22-36
Authors: Paolo Terenziani , Antonella Andolina
Conference Name: The International Conference on Database, Data Warehouse, Data Mining and Big Data (DDDMBD2015)
- Indonesia


Time-varying data are important in many applications. Starting from the 80’s, they have been widely studied in the field of temporal databases. More recently, data warehouses (DWs) have gained an increasing importance, strongly focusing on time-varying data. DWs support different temporal granularities (e.g., days, months, years), as well as several operators for aggregating data along them. In the past two decades, the importance of coping also with user-defined granularities has been clearly identified. However, most current DWs only supports the treatment of limited sets of pre-defined granularities. In this paper, we ground our approach on some basic results in the temporal database literature, including the telic\atelic distinction, and we propose a general and application-independent framework supporting aggregation of measures along user-defined granularities.