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Release - October 24th, 2022

· 3 min read

✨ New ✨​

dbt Integration v2 (transform-tools)​

Details

The new transform-tools version 1.1.0 comes with a big new feature: support for dbt configs.

To begin using dbt configs as your model for Transform, you'll need to do the following:

1. Add a profiles.yml to your dbt project repository if you haven't already, and check it in​

Note: any profile values which are sensitive will need to be replaced with loading from environment variables. Here is an example of our profiles.yml for our internal testing:

transform_dbt:
  target: dev
  outputs:
    dev:
      type: snowflake
      account: "{{ env_var('SNOWFLAKE_ACCOUNT') }}"

      # User/password auth
      user:   "{{ env_var('DBT_DEV_USER') }}"
      password: "{{ env_var('DBT_DEV_USER_PASSWORD') }}"

      role: SYSADMIN
      database: TRANSFORM_ANALYTICS_DB
      warehouse: TEST
      schema: "{{ env_var('DBT_DEV_SCHEMA') }}"
      threads: 1
      client_session_keep_alive: False
    prod:
      type: snowflake
      account: "{{ env_var('SNOWFLAKE_ACCOUNT') }}"

      # User/password auth
      user: "{{ env_var('DBT_PROD_USER') }}"
      password: "{{ env_var('DBT_PROD_USER_PASSWORD') }}"

      role: SYSADMIN
      database: TRANSFORM_ANALYTICS_DB
      warehouse: TEST
      schema: prod_dbt
      threads: 1
      client_session_keep_alive: False

2. Add a GitHub workflow (or equivalent) like the following:​

name: Commit Configs
on:
  push:
    branches: [master,main]
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - uses: actions/setup-python@v2
        with:
          python-version: '3.8.5' # arbitrarily chosen
          architecture: 'x64' # optional x64 or x86. Defaults to x64 if not specified
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install "transform_tools[dbt-snowflake]"
          dbt deps
      - name: Run commit script
        run: python -m transform_tools.validate commit
        env:
          REPO: ${{ github.repository }}
          TRANSFORM_API_KEY: ${{ secrets.TRANSFORM_API_KEY }}
          IS_DBT_PROJECT: "true"
          TFD_DBT_TARGET: prod
          SNOWFLAKE_ACCOUNT: ${{ secrets.SNOWFLAKE_ACCOUNT }}
          DBT_PROD_USER: ${{ secrets.DBT_PROD_USER }}
          DBT_PROD_USER_PASSWORD: ${{ secrets.DBT_PROD_USER_PASSWORD }}

Some notes:

  • We’re installing a dbt adapter because it is required. Here, we’re installing dbt-snowflake.
    • Currently, we support dbt-snowflake, dbt-postgres, dbt-redshift, and dbt-bigquery.
  • We’re loading our sensitive environment variable information from GitHub secrets.
  • We’re overriding the dbt target with TFD_DBT_TARGET to prod because the default target for our profile is dev.

3. Add sensitive information to GitHub secrets (or equivalent)​

4. Push the changes from steps 1 & 2 to your repository​

Private Metrics​

Details

There are likely certain metrics in your organization that should only be visible to particular individuals or teams. Private metrics give metric owners the ability to manage the visibility permissions of metrics for users in your organization.

This is currently an opt-in feature, meaning that we are only turning it on for customers who request it. If you would like us to enable the private metrics feature for your organization, please let us know.

For more information about private metrics, see the documentation here

Boards Section on Metric Page​

Details

Discovering relevant Boards just got even easier. Under each metric page, you will now see a section that displays a list of Boards that contain that metric. Clicking into a Board card will open the Board page.

For more information, see the documentation here