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.

dbt-iomete

The dbt-iomete package contains all the code enabling dbt to work with iomete.

This adapter is forked from the dbt-spark

Getting started

Installation

pip install dbt-iomete

Alternatively, you can install the package from GitHub with:

pip install git+https://github.com/iomete/dbt-iomete.git

Profile Setup

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.