Update index.md

docs/modeling-your-data/modeling-your-data-with-dbt/dbt-operation/lakes/index.md

@@ -27,7 +27,7 @@ At time of writing, `Iceberg` is the preferred file format for Snowflake [iceber
 Note that compared to the other loaders for Snowflake, that field names in Self-describing events and Entities are converted to `snake_case` format (the other loaders retain the format used in the schema, often `camelCase`). You will need to adjust other variables and inputs accordingly compared to what you may find in the docs. 
 
 # Spark
-At time of writing, `Iceberg` is the supported file format for Spark external tables. We've tested this using Glue and Thrift as a connection method. If you create an external table from this lake format in Spark, you should be able to run the models by pointing the model at this table. For more information on setting up dbt with Spark using Thrift, please refer to the [dbt Spark documentation on Thrift](https://docs.getdbt.com/docs/core/connect-data-platform/spark-setup#thrift).
+At time of writing, `Iceberg` is the supported file format for Spark external tables. We've tested this using Glue and Thrift as a connection method. If you have your event data in Iceberg format in a lake, you should be able to run the models by pointing the packages to a spark deployment, connected to that lake. For more information on setting up dbt with Spark using Thrift, please refer to the [dbt Spark documentation on Thrift](https://docs.getdbt.com/docs/core/connect-data-platform/spark-setup#thrift).
 
 # Redshift (spectrum)
 Currently using Redshift Spectrum tables is not supported for our packages due to [limitations](https://docs.aws.amazon.com/redshift/latest/dg/nested-data-restrictions.html) with the platform.