diff --git a/dags/sources/tasks/airflow_logic/db_write_suggestion_task.py b/dags/sources/tasks/airflow_logic/db_write_type_action_suggestions_task.py
similarity index 79%
rename from dags/sources/tasks/airflow_logic/db_write_suggestion_task.py
rename to dags/sources/tasks/airflow_logic/db_write_type_action_suggestions_task.py
index f372d0e0b..cdc1e5e25 100644
--- a/dags/sources/tasks/airflow_logic/db_write_suggestion_task.py
+++ b/dags/sources/tasks/airflow_logic/db_write_type_action_suggestions_task.py
@@ -2,21 +2,23 @@
 
 from airflow import DAG
 from airflow.operators.python import PythonOperator
-from sources.tasks.business_logic.db_write_suggestion import db_write_suggestion
+from sources.tasks.business_logic.db_write_type_action_suggestions import (
+    db_write_type_action_suggestions,
+)
 from utils import logging_utils as log
 
 logger = logging.getLogger(__name__)
 
 
-def db_write_suggestion_task(dag: DAG) -> PythonOperator:
+def db_write_type_action_suggestions_task(dag: DAG) -> PythonOperator:
     return PythonOperator(
         task_id="db_write_suggestion",
-        python_callable=db_write_suggestion_wrapper,
+        python_callable=db_write_type_action_suggestions_wrapper,
         dag=dag,
     )
 
 
-def db_write_suggestion_wrapper(**kwargs) -> None:
+def db_write_type_action_suggestions_wrapper(**kwargs) -> None:
     dag_name = kwargs["dag"].dag_display_name or kwargs["dag"].dag_id
     run_id = kwargs["run_id"]
     dfs_acteur = kwargs["ti"].xcom_pull(task_ids="db_data_prepare")
@@ -40,7 +42,7 @@ def db_write_suggestion_wrapper(**kwargs) -> None:
         kwargs["ti"].xcom_push(key="skip", value=True)
         return
 
-    return db_write_suggestion(
+    return db_write_type_action_suggestions(
         dag_name=dag_name,
         run_id=run_id,
         df_acteur_to_create=df_acteur_to_create,
diff --git a/dags/sources/tasks/airflow_logic/operators.py b/dags/sources/tasks/airflow_logic/operators.py
index a17e0052e..ad4cddfb6 100755
--- a/dags/sources/tasks/airflow_logic/operators.py
+++ b/dags/sources/tasks/airflow_logic/operators.py
@@ -8,7 +8,7 @@
     db_read_propositions_max_id_task,
 )
 from sources.tasks.airflow_logic.db_write_suggestion_task import (
-    db_write_suggestion_task,
+    db_write_type_action_suggestions_task,
 )
 from sources.tasks.airflow_logic.propose_acteur_changes_task import (
     propose_acteur_changes_task,
@@ -93,5 +93,5 @@ def eo_task_chain(dag: DAG) -> None:
         create_tasks,
         propose_services_sous_categories_task(dag),
         db_data_prepare_task(dag),
-        db_write_suggestion_task(dag),
+        db_write_type_action_suggestions_task(dag),
     )
diff --git a/dags/sources/tasks/business_logic/db_data_prepare.py b/dags/sources/tasks/business_logic/db_data_prepare.py
index 98e804a49..c2e5e216e 100644
--- a/dags/sources/tasks/business_logic/db_data_prepare.py
+++ b/dags/sources/tasks/business_logic/db_data_prepare.py
@@ -23,12 +23,6 @@ def db_data_prepare(
     df_acteur_to_delete["suggestion"] = df_acteur_to_delete[
         update_actors_columns
     ].apply(lambda row: json.dumps(row.to_dict(), default=str), axis=1)
-    # Created or updated Acteurs
-    # df_acteur_services = (
-    #     df_acteur_services
-    #     if df_acteur_services is not None
-    #     else pd.DataFrame(columns=["acteur_id", "acteurservice_id"])
-    # )
 
     if df_acteur.empty:
         raise ValueError("df_acteur est vide")
diff --git a/dags/sources/tasks/business_logic/db_write_suggestion.py b/dags/sources/tasks/business_logic/db_write_type_action_suggestions.py
similarity index 98%
rename from dags/sources/tasks/business_logic/db_write_suggestion.py
rename to dags/sources/tasks/business_logic/db_write_type_action_suggestions.py
index 2e921599d..24d48931b 100644
--- a/dags/sources/tasks/business_logic/db_write_suggestion.py
+++ b/dags/sources/tasks/business_logic/db_write_type_action_suggestions.py
@@ -9,7 +9,7 @@
 logger = logging.getLogger(__name__)
 
 
-def db_write_suggestion(
+def db_write_type_action_suggestions(
     dag_name: str,
     run_id: str,
     df_acteur_to_create: pd.DataFrame,