Unified RAG dbt Package
This dbt package transforms data from Fivetran's Unified RAG connector into analytics-ready tables.
Resources
- Number of materialized models¹: 40
- Connector documentation
- dbt package documentation
What does this dbt package do?
This package enables you to generate unstructured document data for Retrieval Augmented Generation (RAG) applications and combine data from HubSpot deals, Jira issues, and Zendesk tickets. It creates enriched models with metrics focused on text chunks prepared for semantic search and LLM workflows.
Note: Redshift destinations are not currently supported due to the stringent character limitations within string datatypes. If you would like Redshift destinations to be supported, please comment within our logged Feature Request.
Output schema
Final output tables are generated in the following target schema:
<your_database>.<connector/schema_name>_unified_rag
Final output tables
By default, this package materializes the following final tables:
| Table | Description |
|---|---|
| rag__unified_document | Prepares text content from multiple data sources into searchable chunks that enable natural language queries through AI chatbots, making your data easily accessible through conversational questions. Example Analytics Questions:
|
¹ Each Quickstart transformation job run materializes these models if all components of this data model are enabled. This count includes all staging, intermediate, and final models materialized as view, table, or incremental.
Prerequisites
To use this dbt package, you must have the following:
- At least one of the below support Fivetran connections syncing data into your destination.
- HubSpot (specifically deals)
- Jira
- Zendesk Support
- A Snowflake, BigQuery, Databricks, or PostgreSQL destination.
- Redshift destinations are not currently supported due to the stringent character limitations within string datatypes. If you would like Redshift destinations to be supported, please comment within our logged Feature Request.
How do I use the dbt package?
You can either add this dbt package in the Fivetran dashboard or import it into your dbt project:
- To add the package in the Fivetran dashboard, follow our Quickstart guide.
- To add the package to your dbt project, follow the setup instructions in the dbt package's README file to use this package.
How is this package maintained and can I contribute?
Package Maintenance
The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend you stay consistent with the latest version of the package and refer to the CHANGELOG and release notes for more information on changes across versions.
Contributions
A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions.
We highly encourage and welcome contributions to this package. Learn how to contribute to a package in dbt's Contributing to an external dbt package article.