Hevo ingests your data from sources, applies transformations on it and brings it to Schema Mapper. In Schema Mapper you can define how your data will be stored in your destination warehouse.
You can use Hevo’s Schema Mapper to do the following:
- Map an incoming event type to a destination table. All the data for that event type will be stored in the mapped destination table.
- Omit unwanted fields from storing in the destination table. This is especially useful to hide sensitive information like your user’s personal details and financial information. You can also use it to omit large text fields like descriptions, summaries, and comments.
- Flatten your nested objects into a de-normalized destination table. Mapper automatically suggests a denormalized flat structure for your incoming nested objects.
- Compress long names of Events and Event Types meaningfully to fit the character limit set for table and column names in the Destination.
Apart from giving you the above functionalities, Schema Mapper can also do the following for you:
- Create tables with compatible and optimal data types in your destination warehouse.
- Mark incompatible incoming events as Failed for investigation.
Hevo can automatically create and manage all Mappings if you enable Auto Mapping for a pipeline. However, if you wish to manage mapping for a pipeline manually, read Using Schema Mapper. Note: Hevo validates the length of the name even during manual creation of Destination tables and columns. An error is displayed if the length exceeds the defined limit.
- Articles in this section
- Using Schema Mapper
- Mapping Statuses
- Mapping a Source Event Type with a Destination Table
- Mapping a Source Event Type Field with a Destination Table Column
- Resizing String Columns in the Destination
- Fixing Unmapped Fields
- Resolving Incompatible Schema Mappings
- Bulk Actions in Schema Mapper
- Auto Mapping Event Types
- Creating File Partitions for S3 Destination through Schema Mapper
- Schema Mapper Compatibility Table