Controlling the Correctness of Aggregation Operations During Sessions of Interactive Analytic Queries

We present a comprehensive set of conditions and rules to control the correctness aggregation queries within an interactive data analysis session. The goal is extend self-service preparation Business Intelligence (BI) tools automatically detect semantically incorrect aggregate on analytic tables views built by using common operations including filter, project, join, aggregate, union, difference, pivot. introduce aggregable properties describe for any attribute table, which functions correctly along sets dimension attributes. These can also be used formally identify attributes that are summarizable with respect some function given This particularly helpful aggregations measures obtained through use non-distributive like average count. notion summarizability introducing new generalized condition after operation. Finally, we define propagation transform query input into result tables, preserving summarizability.