The Temporal Data Explorer

 Create a Temporal Data Explorer that allows users to investigate how events, measurements, and business metrics change over time. Import CSV files, database extracts, event logs, and timestamped records. Automatically identify time fields, missing intervals, duplicate events, seasonality candidates, sudden shifts, and relationships between multiple timelines. Let users zoom between granular and long-term views, compare periods, annotate important events, and investigate unusual changes. Include configurable aggregation, timezone handling, and exportable charts with reproducible filters. Clearly distinguish correlation from causation, preserve the original timestamps, and label statistical alerts as candidates for investigation rather than proven anomalies or explanations.