Maia help

The {{ no such element: dict object['component_name'] }} orchestration component uses the Connect and Configure parameters to create a table of {{ no such element: dict object['service_name'] }} data, which is then stored in your preferred storage location (Snowflake, Databricks, Amazon Redshift, or cloud storage). You do not need to use the Create Table component when using this connector, as the {{ no such element: dict object['component_name'] }} component will create a new table or replace an existing table for you using the Destination parameters you define.

The {{ no such element: dict object['component_name'] }} orchestration component runs SQL queries on an accessible database, and copies the results to a table via storage. You can query cloud or on-premises databases, so long as they are network-accessible. You can stage data (load data into a table) with this component, to perform further processing and transformations on it. The target table should be considered temporary, because it will either be truncated or recreated each time the component runs. You do not need to set up a Create Table component before using this component.

This page describes how to configure the {{ no such element: dict object['service_name'] }} connector component as part of a data pipeline within Designer. The {{ no such element: dict object['component_name'] }} component uses the Connect and Configure parameters to create a table of {{ no such element: dict object['service_name'] }} data, which is then stored in your preferred storage location (Snowflake, Databricks, Amazon Redshift, or cloud storage). You do not need to use the Create Table component when using this connector, as the {{ no such element: dict object['component_name'] }} component will create a new table or replace an existing table for you using the Destination parameters you define.

This page describes how to configure your custom connector component as part of a data pipeline within Designer. Custom connector components uses the Connect and Configure parameters to create a table of data from the service you custom connector connects to, which is then stored in your preferred storage location (Snowflake, Databricks, Amazon Redshift, or cloud storage). You do not need to use the Create Table component when using this connector, as the custom connector component will create a new table or replace an existing table for you using the Destination parameters you define.

The {{ no such element: dict object['component_name'] }} component uses the Connect and Configure parameters to create a table of {{ no such element: dict object['service_name'] }} data, which is then stored in your preferred storage location (Snowflake, Databricks, or Amazon Redshift). You do not need to use the Create Table component when using this connector, as each time the {{ no such element: dict object['component_name'] }} component runs, the target table is recreated, dropping any existing table of the same name.

Once the component has run once, you can use transformation pipelines to transform your data to fit your business requirements.