The correct answer is C — Enable schema evolution.

When new columns are added to the source data, a pipeline without schema evolution treats the unexpected columns as a schema mismatch and fails the write. Schema evolution, when enabled in an SDP pipeline, automatically adds those new columns to the target Delta table on the next pipeline run. The pipeline continues without intervention, and no historical data is lost.

Option A (disable schema enforcement) is the wrong lever — it removes all schema validation, which could allow corrupt or mistyped data into Table1. Schema evolution is a targeted, safer response.

Option B (row filters to exclude records with new columns) would silently discard valid records just because they carry extra fields — that ' s data loss. Option D (separate table per schema version) creates an explosion of tables as schemas evolve and makes downstream analytics significantly more complex. Schema evolution is the clean, built-in solution.