With the emergence of modern database technologies, the concept of multi-granular data warehousing, which stores data at multiple levels of granularity has become important. In order to store multigranular data, the existing data warehousing schemas, such as star and snowflake are unable to provide support, for the reason that they are designed to store data at a single level of granularity. In this paper, we present a multi-dimensional and multi-granular data warehousing schema (MMDW). MMDW is based on Relational OLAP (ROLAP) and uses a RDBMS to manage new and old (aggregated) data by means of an extended star schema. In contrast to traditional ROLAP, MMDW also allows pre-computation and storage of data at multiple levels of granularity. Furthermore, MMDW is evaluated based on a real world case study and results show that MMDW performs well in terms of aggregation query speed, aggregation query complexity as well as storage used and compares favorably with standard star schema.
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