diff --git a/cdisc_rules_engine/dataset_builders/dataset_metadata_define_dataset_builder.py b/cdisc_rules_engine/dataset_builders/dataset_metadata_define_dataset_builder.py
index 177ed5c5c..d36838a5e 100644
--- a/cdisc_rules_engine/dataset_builders/dataset_metadata_define_dataset_builder.py
+++ b/cdisc_rules_engine/dataset_builders/dataset_metadata_define_dataset_builder.py
@@ -1,3 +1,4 @@
+from cdisc_rules_engine.models.dataset import DatasetInterface
 from cdisc_rules_engine.services import logger
 from cdisc_rules_engine.dataset_builders.base_dataset_builder import BaseDatasetBuilder
 import os
@@ -55,9 +56,15 @@ def build(self):
             if self.dataset_metadata.full_path
             else None
         )
-        matching_row = merged_cleaned[
+        matching_row: DatasetInterface = merged_cleaned[
             merged_cleaned["dataset_location"].str.lower() == dataset_filename
         ]
+        if matching_row.empty:
+            # when using DASK dataset_filename refers to temp parquet filename
+            matching_row: DatasetInterface = merged_cleaned[
+                merged_cleaned["dataset_location"].str.lower()
+                == self.dataset_metadata.original_path.lower()
+            ]
         for column in merged.columns:
             merged[column] = matching_row[column].iloc[0]
         return merged
@@ -93,20 +100,22 @@ def _get_dataset_dataframe(self):
         else:
             datasets = self.dataset_implementation()
             for dataset in self.datasets:
+                ds_metadata = None
                 try:
                     ds_metadata = self.data_service.get_dataset_metadata(
-                        dataset.filename
+                        dataset_name=dataset.filename
+                    )
+                    ds_metadata.data["dataset_domain"] = getattr(
+                        dataset, "domain", None
                     )
-                    ds_metadata.data["dataset_domain"] = dataset.domain
                 except Exception as e:
                     logger.trace(e)
                     logger.error(f"Error: {e}. Error message: {str(e)}")
-                datasets.data = (
-                    ds_metadata.data
-                    if datasets.data.empty
-                    else datasets.data.append(ds_metadata.data)
-                )
-
+                if ds_metadata:
+                    if datasets.data.empty:
+                        datasets.data = ds_metadata.data.copy()
+                    else:
+                        datasets.data = datasets.concat(ds_metadata).data
             if datasets.data.empty or len(datasets.data) == 0:
                 dataset_df = self.dataset_implementation(columns=dataset_col_order)
                 logger.info(f"No datasets metadata is provided for {__name__}.")
diff --git a/cdisc_rules_engine/services/data_services/dummy_data_service.py b/cdisc_rules_engine/services/data_services/dummy_data_service.py
index f22247f97..f163b0a14 100644
--- a/cdisc_rules_engine/services/data_services/dummy_data_service.py
+++ b/cdisc_rules_engine/services/data_services/dummy_data_service.py
@@ -4,7 +4,7 @@
 
 import os
 import pandas as pd
-
+import tempfile
 from cdisc_rules_engine.dummy_models.dummy_dataset import DummyDataset
 from cdisc_rules_engine.exceptions.custom_exceptions import (
     DatasetNotFoundError,
@@ -156,7 +156,22 @@ def __get_dataset_metadata(self, dataset_name: str, **kwargs) -> dict:
         return metadata_to_return
 
     def to_parquet(self, file_path: str) -> str:
-        return ""
+        """
+        Save the dataset with full_path == file_path to a parquet file.
+        Returns the number of rows and the path to the saved parquet file, or (0, "") if not found.
+        """
+        for dataset in self.data:
+            if hasattr(dataset, "full_path") and dataset.full_path == file_path:
+                # Convert the DummyDataset's data (assumed to be a DataFrame or dict-like) to a pandas DataFrame
+                if hasattr(dataset, "data"):
+                    df = pd.DataFrame(dataset.data)
+                else:
+                    # fallback: try to convert the whole object to dict
+                    df = pd.DataFrame([dataset.__dict__])
+                temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".parquet")
+                df.to_parquet(temp_file.name)
+                return len(df.index), temp_file.name
+        return 0, ""
 
     def get_datasets(self) -> Iterable[SDTMDatasetMetadata]:
         return self.data
diff --git a/tests/unit/test_rules_engine.py b/tests/unit/test_rules_engine.py
index 8573651cb..c27468bfb 100644
--- a/tests/unit/test_rules_engine.py
+++ b/tests/unit/test_rules_engine.py
@@ -1278,33 +1278,29 @@ def test_validate_single_dataset_not_equal_to(
             PandasDataset(
                 pd.DataFrame.from_dict(
                     {
-                        "dataset_name": [
-                            "AE",
-                        ],
-                        "dataset_label": [
-                            "Adverse Events",
-                        ],
-                        "dataset_location": [
-                            "te.xpt",
-                        ],
+                        "dataset_name": ["AE"],
+                        "dataset_label": ["Adverse"],
+                        "dataset_location": ["ae.xpt"],
                     }
                 )
             ),
             [
                 {
-                    "executionStatus": "skipped",
+                    "executionStatus": "success",
                     "dataset": "ae.xpt",
                     "domain": "AE",
-                    "variables": [],
-                    "message": "rule evaluation error - evaluation dataset failed to build",
+                    "variables": ["dataset_label", "dataset_location", "dataset_name"],
+                    "message": "Dataset metadata does not correspond to Define XML",
                     "errors": [
                         {
+                            "value": {
+                                "dataset_name": "AE",
+                                "dataset_location": "ae.xpt",
+                                "dataset_label": "Adverse",
+                            },
                             "dataset": "ae.xpt",
-                            "error": "Error occurred during dataset building",
-                            "message": "Failed to build dataset for rule validation. Builder: "
-                            "DatasetMetadataDefineDatasetBuilder, Dataset: AE, "
-                            "Error: single positional indexer is out-of-bounds",
-                        }
+                            "row": 1,
+                        },
                     ],
                 }
             ],
@@ -1320,15 +1316,9 @@ def test_validate_single_dataset_not_equal_to(
             PandasDataset(
                 pd.DataFrame.from_dict(
                     {
-                        "dataset_name": [
-                            "AE",
-                        ],
-                        "dataset_label": [
-                            "Adverse Events",
-                        ],
-                        "dataset_location": [
-                            "ae.xpt",
-                        ],
+                        "dataset_name": ["AE"],
+                        "dataset_label": ["Adverse Events"],
+                        "dataset_location": ["ae.xpt"],
                     }
                 )
             ),
@@ -1372,6 +1362,7 @@ def test_validate_dataset_metadata_against_define_xml(
         first_record={"DOMAIN": "AE"},
         full_path="CDISC01/test/ae.xpt",
         filename="ae.xpt",
+        original_path="ae.xpt",
     )
     validation_result: List[dict] = RulesEngine(
         standard="sdtmig"