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.

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.

Abstract: Various embodiments of systems and methods for monitoring a system are described herein. A request is received from a user to generate a system watch for monitoring a system. The request may include a primary system monitoring parameter to be included in the system watch. One or more system monitoring parameters correlated to the primary system watch are identified from a system monitoring parameter database. The system watch is generated based on the primary system monitoring parameter and at least one secondary system monitoring parameter from the identified one or more system monitoring parameters. In one aspect, the system monitoring parameter database is built based on system watch related input received for a plurality of system watches.