Table of Contents

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  1. Preface
  2. Part 1: Getting Started with Snowflake Data Cloud Connector
  3. Part 2: Data Integration with Snowflake Data Cloud Connector
  4. Part 3: SQL ELT with Snowflake Data Cloud Connector
  5. Appendix A: Data type reference
  6. Appendix B: Additional runtime configurations
  7. Appendix C: Upgrading to Snowflake Data Cloud Connector

Snowflake Data Cloud Connector

Snowflake Data Cloud Connector

Mappings for Snowflake Data Cloud

Mappings for Snowflake Data Cloud

When you configure a mapping, you describe the flow of data from the source to the target. A mapping defines reusable data flow logic that you can use in mapping tasks.
When you create a mapping, you define the Source, Target, and Lookup transformations to represent a Snowflake Data Cloud object. Use the Mapping Designer in Data Integration to add the Source, Target, or Lookup transformations in the mapping canvas and configure the source, target, and lookup properties. To create a mapping, select
Mapping
as the mapping type in the Mapping Designer.
When you run a Snowflake mapping task
based on either a mapping or a mapping in advanced mode
and it completes, you can view the number of processed and failed rows for each source and target in the job details page.
This chapter provides instructions on configuring mappings
and mappings in advanced mode
for Snowflake Data Cloud. You can add mappings
and mappings in advanced mode
to the mapping task and enable SQL ELT optimization in the mapping task. For more information, see SQL ELT optimization for mapping tasks.
You can also create a mapping in SQL ELT mode when your source and target are in the same cloud ecosystem and you want to perform the data transformation entirely within the cloud ecosystem. For more information about mappings in SQL ELT mode, see Mappings in SQL ELT mode for Snowflake Data Cloud.

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