```json { "classifications": [ { "column": "reading_id", "role": "identifier", "confidence": 1.0, "reason": "Primary key with unique VARCHAR values (mr_ prefix) identifying each reading row" }, { "column": "metric_id", "role": "identifier", "confidence": 1.0, "reason": "Foreign key referencing metrics table (m_ prefix), used for JOINs despite low cardinality" }, { "column": "period_start", "role": "dimension", "confidence": 1.0, "reason": "Date values used for time-based grouping and filtering (24 distinct periods)" }, { "column": "segment", "role": "dimension", "confidence": 1.0, "reason": "Categorical values (state codes like AC, AL, AM) used for slicing and grouping" }, { "column": "numerator", "role": "measure", "confidence": 1.0, "reason": "Numeric quantity that can be aggregated (sum/avg) in metric calculations" }, { "column": "denominator", "role": "measure", "confidence": 1.0, "reason": "Numeric quantity that can be aggregated (sum/avg) in metric calculations" }, { "column": "n", "role": "measure", "confidence": 1.0, "reason": "Count/sample size metric that can be summed or averaged across groups" }, { "column": "value", "role": "measure", "confidence": 1.0, "reason": "Computed metric value (likely numerator/denominator) to be aggregated" }, { "column": "computed_at", "role": "dimension", "confidence": 0.9, "reason": "Timestamp for filtering/grouping by computation time (2 distinct batches)" }, { "column": "batch_id", "role": "identifier", "confidence": 0.95, "reason": "Batch identifier for tracking computation runs, used for filtering/joining" }, { "column": "sql_fingerprint", "role": "identifier", "confidence": 0.9, "reason": "Hash/code identifying the SQL query used, serves as technical identifier" } ] } ```