In this chapter, we discuss how using co-operative query languages can be used to increase efficiency of analytics when it’s used on Concept Hierarchies. Concept Hierarchy presents the information of a same dimension in different abstracted levels. This abstraction allows us to identify the same data in multiple granularities and from different users’ perspectives. Conventional query execution retrieves information in one abstracted form only for the given dimension. Actually traditional database management models including RDBMS do not store the concept hierarchy information. This would be more relevant for online analytic processing (OLAP) on data warehouse. Indeed, it is a challenge for designer of data analytics application software to use a query language to take the benefit of concept hierarchy towards extracting optimized information for specific users. In the rest of the chapter, we have explored cooperative query language in this context and establish its suitability.
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