diff --git a/ax/core/observation.py b/ax/core/observation.py
index 6732d00cbcb..5b91f0b2774 100644
--- a/ax/core/observation.py
+++ b/ax/core/observation.py
@@ -468,6 +468,7 @@ def observations_from_data(
     latest_rows_per_group: int | None = None,
     limit_rows_per_metric: int | None = None,
     limit_rows_per_group: int | None = None,
+    load_only_completed_map_metrics: bool = True,
 ) -> list[Observation]:
     """Convert Data (or MapData) to observations.
 
@@ -501,6 +502,8 @@ def observations_from_data(
             uses MapData.subsample() with `limit_rows_per_group` on the first
             map_key (map_data.map_keys[0]) to subsample the MapData. Ignored if
             `latest_rows_per_group` is specified.
+        load_only_completed_map_metrics: If True, only loads the last observation
+            for each completed MapMetric.
 
     Returns:
         List of Observation objects.
@@ -511,7 +514,8 @@ def observations_from_data(
         statuses_to_include_map_metric = NON_ABANDONED_STATUSES
     is_map_data = isinstance(data, MapData)
     map_keys = []
-    if is_map_data:
+    take_map_branch = is_map_data and not load_only_completed_map_metrics
+    if take_map_branch:
         data = assert_is_instance(data, MapData)
         map_keys.extend(data.map_keys)
         if latest_rows_per_group is not None:
@@ -526,7 +530,7 @@ def observations_from_data(
         df = data.map_df
     else:
         df = data.df
-    feature_cols = get_feature_cols(data, is_map_data=is_map_data)
+    feature_cols = get_feature_cols(data, is_map_data=take_map_branch)
     return _observations_from_dataframe(
         experiment=experiment,
         df=df,
diff --git a/ax/modelbridge/base.py b/ax/modelbridge/base.py
index f02cee14aa0..44c6b52411e 100644
--- a/ax/modelbridge/base.py
+++ b/ax/modelbridge/base.py
@@ -306,6 +306,7 @@ def _prepare_observations(
             statuses_to_include=self.statuses_to_fit,
             statuses_to_include_map_metric=self.statuses_to_fit_map_metric,
             map_keys_as_parameters=map_keys_as_parameters,
+            load_only_completed_map_metrics=self._fit_only_completed_map_metrics,
         )
 
     def _transform_data(