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Different Kinds of Hierarchies in Multidimensional Models
Abstract
In the database design, the advantages of using conceptual models for representing users’ requirements are well known. Nevertheless, even though data warehouses (DWs) are databases that store historical data for analytical purposes, they are usually represented at the logical level using the star and snowflake schemas. These schemas facilitate delivery of data for online analytical processing (OLAP) systems. In particular, hierarchies are important since traversing them, OLAP tools perform automatic aggregations of data using the roll-up and drill-down operations. The former operation transforms detailed data into aggregated ones (e.g., daily into monthly sales) while the latter does the opposite.
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