**Classification of `raw.iris` (9 columns)** The profiling results (`analytics.column_overview` and `inspect_columns`) cover the five data columns. The four `_ingestion…` and `_batch/_source…` columns come from the dataset card's column list and types, which I did not profile. **Numeric metrics (4)** All four are DOUBLE, tagged `measure` with aggregation role `measure`, and have no nulls. | Column | Min | Max | |---|---|---| | `sepal_length` | 4.3 | 7.9 | | `sepal_width` | 2.0 | 4.4 | | `petal_length` | 1.0 | 6.9 | | `petal_width` | 0.1 | 2.5 | The profiler labels their `rough_kind` as "text", which is a quirk of its labelling. The physical type is DOUBLE, so they are continuous numeric measurements. **Categorical dimension (1)** - `species` is VARCHAR with semantic role `classifier` and aggregation role `dimension`. It has no nulls and a uniqueness score of 0.02, which matches about 3 distinct values out of 150 rows. It is the natural grouping column and the class label for classification. **Identifiers (0 in the business data)** - No column has a `key_role`, and none is unique per row. The highest uniqueness score is 0.26, for `petal_length`. There is no specimen ID, so the grain of one row per flower has no natural key. - The `_batch_id` (VARCHAR), `_source_file` (VARCHAR) and `_source_system` (VARCHAR) columns are ingestion lineage metadata. They identify where a row was loaded from, not which flower it describes, so they are not business identifiers. **Dates/times (1, technical only)** - `_ingestion_timestamp` (TIMESTAMP) records when each row was loaded. It is not a property of the flowers, and the data has no observation or measurement date. Time-trend questions can therefore only reflect load timing, not anything about the specimens. **Summary:** 4 numeric measures, 1 categorical dimension, 0 true identifiers, and 1 technical timestamp. The other 3 columns are lineage metadata.