Insight generation from statistical measure/dimension combinations

Abstract

Insights gleaned from statistical analysis of a dataset of an in-memory database, may be obtained with high throughput. In response to a user query, a Data Inference Engine (DIE) provides statistically valid measure/dimension combinations of the dataset to an analysis tool. A master procedure may be executed at search query runtime, allowing timely filtering of output of the analysis tool based on columns provided in the user request. Inputs/outputs of the master procedure may avoid storing physical tables, reducing maintenance. The master procedure may comprise individual sub-procedures (e.g. determining outliers, percentage contribution) executed in parallel. Output of sub-procedure(s) may be formatted per a final output format, facilitating union therebetween. Embodiments may filter certain measure/dimension combinations received from the DIE. For example, embodiments may consider only unique measure/dimension combinations (irrespective of dimension order), a limited number of combinations (e.g. ≦20), and/or combinations having a limited number of dimensions (e.g. ≦3).

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