Configuring Automation Coverage

This topic provides steps to configure Automation Coverage across various sources and targets. Automation Coverage offers insights into the achievable auto-conversion percentage for the given source file.

Based on the source and target, when you turn on Automation Coverage toggle it may prompt you to configure it. To configure Automation Coverage, follow the below steps.

Source	Target	Input
Oracle	Amazon Redshift	Select the Output Type as Python.
	Amazon Aurora PostgreSQL	Select the Output Type as SQL.
	Databricks Lakehouse	Select the Output Type as Python 3.
	Databricks Notebook	Select the Output Type as Python.
	Google Big Query	Select the Output Type as Python.
	Hive	Select the Output Type as Java, Scala, or Python.
	Spark	Select the Output Type as Java, Scala, Python 2, or Python 3.
	Snowflake	Select the Output Type as Python or Snowflake Scripting.
Teradata	Amazon Redshift	Select the Output Type as Python or RSQL.
	Databricks Lakehouse	Select the Output Type as Python 3.
	Databricks Notebook	Select the Output Type as Python.
	Google Big Query	Select the Output Type as Python.
	Hive	Select the Output Type as Java, Scala, HPL/SQL, or Python.
	Spark	Select the Output Type as Java, Scala, Python 2, or Python 3.
	Snowflake	Select the Output Type as Python or Snowflake Scripting.
DataStage	AWS Glue Job	Provide Database Name, Schema Name and Prefix. In AWS Glue Catalog Database, provide the AWS Glue Catalog Database connection details to connect the database and schema. In S3 Bucket Base Path, provide the S3 storage repository path where you need to store the source and target files.
	Databricks Lakehouse	Select the Output Type as Python or DBT.
	Databricks Notebook	Nil
	Delta Live Tables	Nil
	Spark	Select the Output Type as Python 2, or Python 3.
	Snowflake	Nil
	AWS Glue Job	Nil
Informatica	AWS Glue Studio	To choose the required databases, turn on Is JDBC Required toggle and then select the required databases such as Oracle, SQL Server, etc. Provide Database Name, Schema Name and Prefix. In AWS Glue Catalog Database, provide the AWS Glue Catalog Database connection details to connect the database and schema. In S3 Bucket Base Path, provide the S3 storage repository path where you need to store the source and target files.
	Databricks Lakehouse	Nil
	Databricks Notebook	Nil
	Delta Live Tables	Nil
	Spark	Enable Spark-Native: External toggle and then select the databases to fetch input data from an external source such as Oracle, Netezza, Teradata, etc., and process that data in Spark, and then move the processed or output data to an external target. Select the Output Type as Python2 or Python 3.