The columns selected in data retrieval queries impact the performance and scalability of both import and DirectQuery data models. For import models, the resources required by the refresh process and the size of the compressed data model are directly impacted by column selection. Specifically, the cardinality of columns drives their individual memory footprint and memory (per column) correlates closely to query duration when these columns are referenced in measures and report visuals. For DirectQuery models, the performance of report queries is directly affected.
Regardless of the model type, how this selection is implemented also impacts the robustness of the retrieval process. Additionally, the names assigned to columns (or accepted from the source) directly impact the Q & A or natural language query experience. This recipe provides examples...