diff --git a/tests/unit/workflow/test_workflow_subgraphs.py b/tests/unit/workflow/test_workflow_subgraphs.py
index d1521dc211..72fae8ef47 100644
--- a/tests/unit/workflow/test_workflow_subgraphs.py
+++ b/tests/unit/workflow/test_workflow_subgraphs.py
@@ -14,7 +14,6 @@
 # limitations under the License.
 #
 
-import glob
 import math
 import os
 
@@ -22,13 +21,11 @@
 import pytest
 from pandas.api.types import is_integer_dtype
 
-import nvtabular as nvt
-from merlin.core import dispatch
 from merlin.core.dispatch import HAS_GPU
 from merlin.core.utils import set_dask_client
 from merlin.dag.ops.subgraph import Subgraph
-from nvtabular import Dataset, Workflow, ops
-from tests.conftest import get_cats
+from nvtabular import Workflow, ops
+from tests.conftest import assert_eq, get_cats
 
 
 @pytest.mark.parametrize("gpu_memory_frac", [0.01, 0.1])
@@ -98,23 +95,12 @@ def get_norms(tar):
     assert len(cats1.tolist()) == len(cats_expected1.tolist())
 
     # Write to new "shuffled" and "processed" dataset
-    workflow.transform(dataset).to_parquet(
-        tmpdir,
-        out_files_per_proc=10,
-        shuffle=nvt.io.Shuffle.PER_PARTITION,
-    )
-
-    dataset_2 = Dataset(glob.glob(str(tmpdir) + "/*.parquet"), part_mem_fraction=gpu_memory_frac)
-
-    df_pp = dispatch.concat(list(dataset_2.to_iter()), axis=0)
+    df_pp = workflow.transform(dataset).to_ddf().compute()
 
     if engine == "parquet":
         assert is_integer_dtype(df_pp["name-cat"].dtype)
     assert is_integer_dtype(df_pp["name-string"].dtype)
 
-    num_rows, num_row_groups, col_names = dispatch.read_parquet_metadata(str(tmpdir) + "/_metadata")
-    assert num_rows == len(df_pp)
-
     subgraph_cat = workflow.get_subgraph("cat_graph")
     subgraph_cont = workflow.get_subgraph("cont_graph")
     assert isinstance(subgraph_cat, Workflow)
@@ -127,3 +113,12 @@ def get_norms(tar):
     with pytest.raises(ValueError) as exc:
         workflow.get_subgraph("not_exist")
     assert "No subgraph named" in str(exc.value)
+
+    sub_cat_df = subgraph_cat.transform(dataset).to_ddf().compute()
+    assert assert_eq(sub_cat_df.reset_index(drop=True), df_pp[cat_names].reset_index(drop=True))
+
+    cont_names = [name + concat_ops for name in cont_names]
+    sub_cont_df = subgraph_cont.transform(dataset).to_ddf().compute()
+    assert assert_eq(
+        sub_cont_df[cont_names].reset_index(drop=True), df_pp[cont_names].reset_index(drop=True)
+    )