diff --git a/backend/dataflow/validate_geometries.py b/backend/dataflow/validate_geometries.py
index 3cd5d15..843df12 100644
--- a/backend/dataflow/validate_geometries.py
+++ b/backend/dataflow/validate_geometries.py
@@ -6,9 +6,9 @@
 class ValidateGeometriesOptions(PipelineOptions):
     @classmethod
     def _add_argparse_args(cls, parser):
-        parser.add_argument('--dataset', required=True)
-        parser.add_argument('--input_bucket', required=True)
-        parser.add_argument('--output_bucket', required=True)
+        parser.add_argument('--dataset')
+        parser.add_argument('--input_bucket')
+        parser.add_argument('--output_bucket')
 
 class ReadParquetDoFn(beam.DoFn):
     def __init__(self, input_bucket):
@@ -23,16 +23,12 @@ def process(self, dataset):
 
 class ValidateGeometriesDoFn(beam.DoFn):
     def process(self, element):
-        import pandas as pd
         from shapely.geometry import Polygon, MultiPolygon
-        
         gdf = element['data']
-        dataset = element['dataset']
         
         # Basic validation for all geometries
         invalid_mask = ~gdf.geometry.is_valid
         if invalid_mask.any():
-            # Attempt to fix invalid geometries
             gdf.loc[invalid_mask, 'geometry'] = gdf.loc[invalid_mask, 'geometry'].apply(
                 lambda geom: geom.buffer(0) if geom else None
             )
@@ -40,30 +36,6 @@ def process(self, element):
         # Ensure all features are valid after fixes
         gdf = gdf[gdf.geometry.is_valid]
         
-        # Ensure all geometries are Polygon or MultiPolygon
-        gdf = gdf[gdf.geometry.apply(lambda x: isinstance(x, (Polygon, MultiPolygon)))]
-        
-        # Remove empty geometries
-        gdf = gdf[~gdf.geometry.is_empty]
-        
-        # Dataset-specific validations
-        if dataset == 'water_projects':
-            if 'area_ha' in gdf.columns:
-                gdf = gdf[gdf.area_ha > 0]
-            if 'budget' in gdf.columns:
-                gdf = gdf[gdf.budget > 0]
-                
-        elif dataset == 'wetlands':
-            if 'gridcode' in gdf.columns:
-                gdf = gdf[gdf.gridcode.notna()]
-            if 'toerv_pct' in gdf.columns:
-                gdf['toerv_pct'] = pd.to_numeric(gdf['toerv_pct'], errors='coerce')
-                gdf = gdf[gdf.toerv_pct.between(0, 100)]
-                
-        elif dataset == 'cadastral':
-            if 'bfe_number' in gdf.columns:
-                gdf = gdf[gdf.bfe_number.notna()]
-        
         # Calculate validation stats
         stats = {
             'total_rows': len(element['data']),
@@ -84,25 +56,16 @@ def process(self, element):
         gdf = element['data']
         stats = element['stats']
         
-        # Write parquet
         output_path = f'gs://{self.output_bucket}/validated/{dataset}/current.parquet'
         logging.info(f'Writing to {output_path}')
-        gdf.to_parquet(
-            output_path,
-            compression='zstd',
-            compression_level=3,
-            index=False,
-            row_group_size=100000
-        )
+        gdf.to_parquet(output_path)
         
-        # Write stats
         stats_path = f'gs://{self.output_bucket}/validated/{dataset}/validation_stats.csv'
         pd.DataFrame([stats]).to_csv(stats_path, index=False)
         
         yield element
 
 def run(argv=None):
-    """Build and run the pipeline."""
     pipeline_options = PipelineOptions(argv)
     options = pipeline_options.view_as(ValidateGeometriesOptions)