diff --git a/datalab/datalab_session/data_operations/data_operation.py b/datalab/datalab_session/data_operations/data_operation.py
index 042535b..a9aa37a 100644
--- a/datalab/datalab_session/data_operations/data_operation.py
+++ b/datalab/datalab_session/data_operations/data_operation.py
@@ -50,7 +50,7 @@ def wizard_description():
         """
 
     @abstractmethod
-    def operate(self, cache_key, input_files):
+    def operate(self):
         """ The method that performs the data operation.
             It should periodically update the percent completion during its operation.
             It should set the output and status into the cache when done.
diff --git a/datalab/datalab_session/data_operations/long.py b/datalab/datalab_session/data_operations/long.py
index 184e769..7f8d77c 100644
--- a/datalab/datalab_session/data_operations/long.py
+++ b/datalab/datalab_session/data_operations/long.py
@@ -36,7 +36,7 @@ def wizard_description():
             }            
         }
     
-    def operate(self, cache_key, input_files):
+    def operate(self):
         num_files = len(self.input_data.get('input_files', []))
         per_image_timeout = ceil(float(self.input_data.get('duration', 60.0)) / num_files)
         for i, file in enumerate(self.input_data.get('input_files', [])):
diff --git a/datalab/datalab_session/data_operations/median.py b/datalab/datalab_session/data_operations/median.py
index 82b494c..e113c8d 100644
--- a/datalab/datalab_session/data_operations/median.py
+++ b/datalab/datalab_session/data_operations/median.py
@@ -38,23 +38,25 @@ def wizard_description():
             }
         }
     
-    def operate(self, cache_key, input_files):
+    def operate(self):
 
-        log.info(f'Executing median operation on {len(input_files)} files')
+        input = self.input_data.get('input_files', [])
 
-        image_data_list = self.get_fits_npdata(input_files, percent=40.0, cur_percent=0.0)
+        log.info(f'Executing median operation on {len(input)} files')
+
+        image_data_list = self.get_fits_npdata(input, percent=0.4, cur_percent=0.0)
 
         stacked_data = stack_arrays(image_data_list)
 
         # using the numpy library's median method
         median = np.median(stacked_data, axis=2)
 
-        hdu_list = create_fits(cache_key, median)
+        hdu_list = create_fits(self.cache_key, median)
 
-        output = self.create_and_store_fits(hdu_list, percent=60.0, cur_percent=40.0)
+        output = self.create_and_store_fits(hdu_list, percent=0.6, cur_percent=0.4)
 
         output =  {'output_files': output}
 
         log.info(f'Median operation output: {output}')
-        self.set_percent_completion(1)
+        self.set_percent_completion(1.0)
         self.set_output(output)
diff --git a/datalab/datalab_session/data_operations/noop.py b/datalab/datalab_session/data_operations/noop.py
index 172a2f5..9905ef4 100644
--- a/datalab/datalab_session/data_operations/noop.py
+++ b/datalab/datalab_session/data_operations/noop.py
@@ -40,7 +40,7 @@ def wizard_description():
             }            
         }
     
-    def operate(self, cache_key, input_files):
+    def operate(self):
         print("No-op triggered!")
         output = {
             'output_files': self.input_data.get('input_files', [])
diff --git a/datalab/datalab_session/tasks.py b/datalab/datalab_session/tasks.py
index 0b8b7f3..18411ca 100644
--- a/datalab/datalab_session/tasks.py
+++ b/datalab/datalab_session/tasks.py
@@ -16,7 +16,4 @@ def execute_data_operation(data_operation_name: str, input_data: dict):
     if operation_class is None:
         raise NotImplementedError("Operation not implemented!")
     else:
-        operation = operation_class(input_data)
-        cache_key = operation.generate_cache_key()
-
-        operation.operate(cache_key, input_data.get('input_files', []))
+        operation_class(input_data).operate()