dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
dbt is the T in ELT. Organize, cleanse, denormalize, filter, rename, and pre-aggregate the raw data in your warehouse so that it's ready for analysis.
The dbt-iomete
package contains all the code enabling dbt to work with iomete.
This adapter is forked from the dbt-spark
pip install dbt-iomete
Alternatively, you can install the package from GitHub with:
pip install git+https://github.com/iomete/dbt-iomete.git
iomete:
target: dev
outputs:
dev:
type: iomete
host: <host>
port: 443
https: true # or http
lakehouse: <serverless_lakehouse_name>
schema: <database_name>
user: "{{ env_var('DBT_IOMETE_USER_NAME') }}"
token: "{{ env_var('DBT_IOMETE_TOKEN') }}"
For more information, consult the docs.