Pardot dbt Package
This dbt package transforms data from Fivetran's Pardot connector into analytics-ready tables.
Resources
- Number of materialized models¹: 21
- Connector documentation
- dbt package documentation
What does this dbt package do?
This package enables you to better understand your Pardot prospects, opportunities, lists, and campaign performance. It creates enriched models with metrics focused on prospect activity and campaign effectiveness.
Output schema
Final output tables are generated in the following target schema:
<your_database>.<connector/schema_name>_pardot
Final output tables
By default, this package materializes the following final tables:
| Table | Description |
|---|---|
| pardot__campaigns | Each record represents a Pardot campaign enriched with aggregated metrics including prospect counts, opportunity counts by status (won/lost), and opportunity amounts by status to measure campaign performance and revenue impact. Example Analytics Questions:
|
| pardot__lists | Each record represents a Pardot list enriched with aggregated activity metrics from list members including email activity counts, visit activity counts, and timestamps of most recent activities to measure list engagement levels. Example Analytics Questions:
|
| pardot__opportunities | Each record represents a Pardot opportunity enriched with the count of associated prospects to connect sales pipeline data with prospect relationships and track opportunity value and progression. Example Analytics Questions:
|
| pardot__prospects | Each record represents a Pardot prospect enriched with aggregated activity metrics including email activity counts, visit activity counts, and configurable activity type metrics to analyze prospect engagement and lead quality. 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 Pardot 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.