This package models Pipedrive data from Airbyte's connector.
Let us know which connectors you would like to see next here
This package contains staging models, with the following naming conventions across all packages:
- Boolean fields are prefixed with
is_
orhas_
- Timestamps are appended with
_timestamp
- ID primary keys are prefixed with the name of the table. For example, the campaign table's ID column is renamed
campaign_id
.
This package contains configurations for DBT metrics for you to get up and running quickly with standard Pipedrive metrics in your existing BI tools.
Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.
Include in your packages.yml
packages:
- package: cerebriumAI/dbt-pipedrive
version: ["0.1.0"]
By default, this package will look for your Pipedrive data in the pipedrive
schema of your target database. If this is not where your Pipedrive data is, please add the following configuration to your dbt_project.yml
file:
# dbt_project.yml
---
config-version: 2
vars:
pipedrive_schema: your_schema_name
pipedrive_database: your_database_name
This package has been tested on BigQuery, Snowflake, Redshift, Postgres, and Databricks.
dbt v0.20.0
introduced a new project-level dispatch configuration that enables an "override" setting for all dispatched macros. If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) dispatch configuration within your dbt_project.yml
. This is required in order for the package to accurately search for macros within the dbt-labs/spark_utils
then the dbt-labs/dbt_utils
packages respectively.
# dbt_project.yml
dispatch:
- macro_namespace: dbt_utils
search_order: ["spark_utils", "dbt_utils"]
Additional contributions to this package are very welcome! Please create issues or open PRs against master
. Check out this post on the best workflow for contributing to a package. Suggestions to the DBT metrics are welcome too!
- Provide feedback on our existing dbt packages or what you'd like to see next
- Join our Slack community where we inform you about changes to packages, our roadmap as well as reach out for any help