Enhance the Azure Analysis Services connector to dynamically generate and push down DAX statistical queries (like MEDIAN and PERCENTILE.INC), enabling natively supported Box Plots and Histograms while keeping data in External (Live) Mode.

The Use Case: As organizations increasingly adopt Microsoft Fabric and centralized Semantic Models (via Azure AS / XMLA endpoints) to handle massive enterprise datasets, Spotfire data scientists need to leverage Spotfire's statistical visualizations directly on top of these models without moving the data.

The Current Limitation: Currently, when connecting to an AS cube or Fabric Semantic Model in External (Live) Mode, Spotfire is unable to render critical statistical visualizations like Box Plots and custom-binned Histograms. While the underlying DAX language natively supports complex statistical functions (such as MEDIAN(), PERCENTILE.INC(), and COUNTROWS()), Spotfire’s Azure AS connector does not dynamically translate the visual requirements into these specific DAX queries for live pushdown. Because of this, users are forced to abandon External Mode and import massive snapshots of row-level data into memory just to calculate a median or view a data distribution.

The Request: Please enhance the query generation engine within the Azure Analysis Services connector. When a user requests a Box Plot, Histogram, or selects statistical aggregations (like Median or Quartiles) on an External data table, the connector should automatically generate the corresponding native DAX statistical queries and push the compute down to the Analysis Services/Fabric backend.

Business Value: Implementing this will unlock Spotfire's core analytical strengths on top of modern, massive data architectures (like Fabric's Direct Lake). It will prevent unnecessary data duplication, reduce Spotfire server memory overhead, and allow data scientists to seamlessly perform distribution analysis on live enterprise data cubes.