**The dataset has no usable time dimension, so there is no growing, shrinking, flat, or seasonal trend to report.** - **Ingestion timestamp:** `_ingestion_timestamp` is the only true timestamp column. Across all 8,500 rows it has exactly 1 distinct value (2026-10-01 03:08:19.556483), from 1 batch and 1 source file. It records when the data was loaded, not when anyone slept, so it can't show a trend. - **Grain:** The table has one row per `user_id`, a single snapshot per person. There are no repeated observations of the same person over time. - **`bedtime_phone_minutes`:** The card lists it as a temporal axis (range 1 to 180), but it measures how many minutes someone spent on their phone at bedtime. It is a duration, not a calendar date, and it is also flagged as person-identifying. - **Other columns:** None of the remaining columns is a date or time. This is a cross-sectional dataset, so the useful questions are comparisons between groups rather than movement over time. For example, you could compare sleep debt, sleep latency, or fatigue by chronotype, bedtime app, occupation, or bedtime phone-minute bands. I can run any of those next.