Qualtrics dbt Package
This dbt package transforms data from Fivetran's Qualtrics connector into analytics-ready tables.
Resources
- Number of materialized models¹: 44
- Connector documentation
- dbt package documentation
What does this dbt package do?
This package enables you to transform core object tables into analytics-ready models and consolidate survey responses with user, question, and survey details. It creates enriched models with metrics focused on surveys, contacts, directories, and distributions.
Output schema
Final output tables are generated in the following target schema:
<your_database>.<connector/schema_name>_qualtrics
Final output tables
By default, this package materializes the following final tables:
| Table | Description |
|---|---|
| qualtrics__contact | Detailed view of all contacts (from both the XM Directory and Research Core contact endpoints), enhanced with response and mailing list metrics. Example Analytics Questions:
|
| qualtrics__daily_breakdown | Provides a daily summary of survey activity including survey sends, responses, and distribution performance to monitor day-to-day engagement and identify trends. Example Analytics Questions:
|
| qualtrics__directory | Manages contact directories with metrics on total contacts, survey distributions sent, and engagement rates to organize audiences and optimize contact list management. Example Analytics Questions:
|
| qualtrics__distribution | Monitors survey distribution campaigns including send methods, recipient counts, and response metrics to optimize distribution strategies and timing. Example Analytics Questions:
|
| qualtrics__response | Provides detailed question-level response data including answers to individual questions and sub-questions, enriched with survey context to analyze response patterns and answer distributions. Example Analytics Questions:
|
| qualtrics__survey | Tracks survey-level metrics including response counts, question counts, distribution details, and survey status to monitor survey performance and response rates. 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 Fivetran Qualtrics connection syncing data into your destination.
- A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.
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.