diff --git a/composer/2022_airflow_summit/data_analytics_dag.py b/composer/2022_airflow_summit/data_analytics_dag.py
index 53dea433f607..a493b6b486ba 100644
--- a/composer/2022_airflow_summit/data_analytics_dag.py
+++ b/composer/2022_airflow_summit/data_analytics_dag.py
@@ -13,6 +13,7 @@
 # limitations under the License.
 
 
+# [START composer_dataanalyticstutorial_dag]
 import datetime
 
 from airflow import models
@@ -46,13 +47,12 @@
             f"{BQ_DESTINATION_DATASET_NAME}.{BQ_DESTINATION_TABLE_NAME}",
             f"{BQ_DESTINATION_DATASET_NAME}.{BQ_NORMALIZED_TABLE_NAME}",
         ],
-
     },
     "environment_config": {
         "execution_config": {
             "service_account": "{{var.value.dataproc_service_account}}"
         }
-    }
+    },
 }
 
 yesterday = datetime.datetime.combine(
@@ -66,7 +66,7 @@
     # To email on failure or retry set 'email' arg to your email and enable
     # emailing here.
     "email_on_failure": False,
-    "email_on_retry": False
+    "email_on_retry": False,
 }
 
 with models.DAG(
@@ -96,7 +96,7 @@
             {"name": "Holiday", "type": "STRING"},
         ],
         skip_leading_rows=1,
-        write_disposition="WRITE_TRUNCATE"
+        write_disposition="WRITE_TRUNCATE",
     )
 
     with TaskGroup("join_bq_datasets") as bq_join_group:
@@ -138,3 +138,4 @@
             )
 
         load_external_dataset >> bq_join_group >> create_batch
+# [END composer_dataanalyticstutorial_dag]
diff --git a/composer/2022_airflow_summit/data_analytics_process.py b/composer/2022_airflow_summit/data_analytics_process.py
index 44e68b5c2f32..6429541a6c3b 100644
--- a/composer/2022_airflow_summit/data_analytics_process.py
+++ b/composer/2022_airflow_summit/data_analytics_process.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-
+# [START composer_dataanalyticstutorial_dataprocjob]
 import sys
 
 
@@ -51,7 +51,8 @@
         # Uses the "overwrite" SaveMode to ensure DAG doesn't fail when being re-run
         # See https://spark.apache.org/docs/latest/sql-data-sources-load-save-functions.html#save-modes
         # for other save mode options
-        df.write.format("bigquery").option("temporaryGcsBucket", temp_path).mode("overwrite").save(
-            WRITE_TABLE
-        )
+        df.write.format("bigquery").option("temporaryGcsBucket", temp_path).mode(
+            "overwrite"
+        ).save(WRITE_TABLE)
         print("Data written to BigQuery")
+# [END composer_dataanalyticstutorial_dataprocjob]