Abstract: A plurality of data fields are obtained from a selected data source. A first subset of the plurality of data fields corresponds to a plurality of measures and a second subset of the plurality of data fields corresponds to a plurality of dimensions. A machine learning model is prompted to generate a plurality of suggested metric objects. In response to prompting the machine learning model, a respective metric definition is generated for each measure in the plurality of measures. Each generated metric definition includes a plurality of data fields, including: (i) a name; (ii) a measure; (iii) a time dimension; and (iv) an aggregation type.

Abstract: A system obtains a bundle of insights generated based on insight templates and provides the bundle of insights as input to a machine learning model. The system then generates a summary of the bundle of insights using the machine learning model.