The table has 300 rows and 23 columns, and it covers no real time period. **Size** - The single table `raw.AI_Usage_and_Impact_on_Students_and_Professionals` has 300 rows, from the row count in the query result. Those rows hold 288 distinct `User_ID` values, so some IDs repeat (about 12 rows beyond one per user). - It has 23 columns, taken from the dataset card rather than a query. Four are ingestion metadata: `_ingestion_timestamp`, `_batch_id`, `_source_file` and `_source_system`. That leaves 19 survey columns, such as demographics, AI tool and purpose, usage hours, cost, and productivity, accuracy and satisfaction scores. **Time period** - None of the 19 survey columns is a date or timestamp. The data is a cross-sectional survey snapshot, so it cannot show trends or change over time. - The only time field is `_ingestion_timestamp`. Every row has the same value, 2026-10-02 09:58:27, from one batch and one source file. That records when the file was loaded, not when the survey responses were collected. Any question about change over time can't be answered from this dataset. Comparisons have to be across groups such as user type, tool or education level.