diff --git a/dags/data_utils/metabase_aggregation/aggregation.py b/dags/data_utils/metabase_aggregation/aggregation.py
index 90e390b..5e8b5c6 100644
--- a/dags/data_utils/metabase_aggregation/aggregation.py
+++ b/dags/data_utils/metabase_aggregation/aggregation.py
@@ -39,6 +39,24 @@ def aggregate_data_for_clients(db_cluster, client_databases, queries):
     df = pd.DataFrame(data)
     return df
 
+def aggregate_data_for_clients_for_unique_query(db_cluster, client_databases, query):
+    """
+    Performs data aggregation for each client and returns a DataFrame.
+    """
+    data = []
+
+    for client_db in client_databases:
+        connection = get_postgres_connection(db_cluster, client_db)
+        result = connection.execute(text(query))
+        df = pd.DataFrame(result)
+        df['client'] = client_db  # Add client name to results
+        data.append(df)
+        connection.close()  # Close the connection after query execution
+
+    # Convert results to DataFrame
+    df = pd.concat(data)
+    return df
+
 def clean_data_in_postgres(connection, table):
     """Deletes rows in the table."""
     try:
@@ -102,12 +120,9 @@ def aggregate_by_date_task():
 
     target_database = "aggregated_client_data"
 
-    for client in client_databases:
-        target_table = f"aggregate_by_date_{client}"
-        connection = get_postgres_connection(db_cluster_prod, client)
-        result = connection.execute(text(query))
-        df = pd.DataFrame(result)
-        insert_data_to_aggregated_db(db_cluster_preprod, df, target_database, target_table)
+    target_table = "aggregate_by_date"
+    df = aggregate_data_for_clients_for_unique_query(db_cluster_prod, client_databases, query)
+    insert_data_to_aggregated_db(db_cluster_preprod, df, target_database, target_table)
 
 def aggregate_by_participation_type_task():
     client_databases = ["angers", "cdc", "cea", "cese", "grand_nancy", "lyon", "marseille", "meyzieu", "sytral", "thionville", "toulouse", "tours", "valbonne"]
@@ -121,10 +136,6 @@ def aggregate_by_participation_type_task():
             """
 
     target_database = "aggregated_client_data"
-
-    for client in client_databases:
-        target_table = f"aggregate_by_participation_type_{client}"
-        connection = get_postgres_connection(db_cluster_prod, client)
-        result = connection.execute(text(query))
-        df = pd.DataFrame(result)
-        insert_data_to_aggregated_db(db_cluster_preprod, df, target_database, target_table)
\ No newline at end of file
+    target_table = "aggregate_by_participation_type"
+    df = aggregate_data_for_clients_for_unique_query(db_cluster_prod, client_databases, query)
+    insert_data_to_aggregated_db(db_cluster_preprod, df, target_database, target_table)
\ No newline at end of file