Update databricks.md

docs/running/databricks.md

@@ -3,12 +3,12 @@ title: Running on Databricks
 parent: Running Zingg on Cloud
 nav_order: 6
 ---
-There are several ways to run Zingg on Databricks
+There are several ways to run Zingg on Databricks. All [file formats and data sources and sinks](../dataSourcesAndSinks) are supported within Databricks. 
 
-# Running directly within Databricks using the notebook interface
+# Running directly within Databricks using the Databricks notebook interface
 This uses the Zingg Python API and an [example notebook is available here](https://github.com/zinggAI/zingg/blob/main/examples/databricks/FebrlExample.ipynb)
 
-# Running using Databricks Connect
+# Running using Databricks Connect from your local machine
 1. Configure databricks connect 11.3 and create correspoding workspace/cluster as per the [Databricks docs](https://docs.databricks.com/dev-tools/databricks-connect-legacy.html). Please makre sure that you run `databricks-connect configure`
 
 2. Set env variable ZINGG_HOME to the path where latest zingg release jar is e.g. location of zingg-0.4.0-SNAPSHOT.jar
@@ -24,8 +24,7 @@ Please refer to the [different options](https://docs.zingg.ai/zingg/stepbystep/z
 
 
 # Running on Databricks using Spark Submit Jobs
-
-The cloud environment does not have the system console for the labeler to work. Zingg is run as a Spark Submit Job along with a python notebook-based labeler specially created to run within the Databricks cloud.
+Zingg is run as a Spark Submit Job along with a python notebook-based labeler specially created to run within the Databricks cloud since the cloud environment does not have the system console for the labeler to work. 
 
 Please refer to the [Databricks Zingg tutorial](https://medium.com/@sonalgoyal/identity-resolution-on-databricks-for-customer-360-591661bcafce) for a detailed tutorial.