diff --git a/viadot/flows/sharepoint_to_adls.py b/viadot/flows/sharepoint_to_adls.py
index 2a2d6adb6..5bca3cc8e 100644
--- a/viadot/flows/sharepoint_to_adls.py
+++ b/viadot/flows/sharepoint_to_adls.py
@@ -7,6 +7,7 @@
 from typing import Literal
 from prefect.backend import set_key_value
 from prefect.utilities import logging
+from prefect.engine.state import Finished
 
 from viadot.task_utils import (
     add_ingestion_metadata_task,
@@ -189,9 +190,20 @@ def slugify(name):
 
 
 @task(slug="check_df")
-def check_if_df_empty(df):
+def check_if_df_empty(df, if_no_data_returned: str = "skip"):
+    # -> to task.utils
+    class NoDataReturnedError(Exception):
+        def __init__(self, message):
+            self.message = message
+
     if len(df.index) == 0:
-        logger.info("No data in the response. Df empty.")
+        if if_no_data_returned == "skip":
+            logger.info("No data in the source response. Df empty.")
+        elif if_no_data_returned == "warn":
+            logger.warning("No data in the source response. Df empty.")
+        elif if_no_data_returned == "fail":
+            raise NoDataReturnedError("No data in the source response. Df empty.")
+        return True
 
 
 class SharepointListToADLS(Flow):
@@ -214,7 +226,7 @@ def __init__(
         output_file_extension: str = ".parquet",
         validate_df_dict: dict = None,
         set_prefect_kv: bool = False,
-        if_no_data_returned: Literal["continue", "warn", "fail"] = "continue",
+        if_no_data_returned: Literal["skip", "warn", "fail"] = "skip",
         *args: List[any],
         **kwargs: Dict[str, Any],
     ):
@@ -290,6 +302,7 @@ def __init__(
         self.vault_name = vault_name
         self.row_count = row_count
         self.validate_df_dict = validate_df_dict
+        self.if_no_data_returned = if_no_data_returned
 
         # AzureDataLakeUpload
         self.adls_dir_path = adls_dir_path
@@ -339,12 +352,18 @@ def gen_flow(self) -> Flow:
             row_count=self.row_count,
             credentials_secret=self.sp_cert_credentials_secret,
         )
+        df_empty = check_if_df_empty.bind(df, self.if_no_data_returned)
+
+        if df_empty:
+            if self.if_no_data_returned == "warn":
+                raise Finished(
+                    "Flow finished because there is no new data for ingestion."
+                )
 
         if self.validate_df_dict:
             validation_task = validate_df(df=df, tests=self.validate_df_dict, flow=self)
             validation_task.set_upstream(df, flow=self)
 
-        check_if_df_empty.bind(df, flow=self)
         df_with_metadata = add_ingestion_metadata_task.bind(df, flow=self)
         dtypes_dict = df_get_data_types_task.bind(df_with_metadata, flow=self)
         df_mapped = df_map_mixed_dtypes_for_parquet.bind(