1. Install the package
Add the Valido dbt package to your `packages.yml` file. Run `dbt deps` to install it alongside your existing dependencies.
Valido + dbt
Your dbt tests, amplified. Move beyond static snapshots to continuous validation with AI-driven data quality.
How it works
A seamless bridge between dbt and data quality
Valido doesn't just sit on top of dbt; it dives in. We read your dbt manifest to understand your project structure, sync your test results in real-time, and extend your coverage with statistical monitoring that runs between scheduled dbt runs.
Manifest & Sync
When you connect Valido to your dbt project, our CLI reads the compiled manifest to map your models, tests, and sources. We then push your dbt test results to Valido's cloud platform, creating a living history of your data health.
Statistical Extension
While dbt tests are powerful, they are discrete snapshots. Valido adds a layer of statistical significance checking that runs continuously, alerting you to distribution shifts or freshness anomalies that occur *between* your regular dbt schedules.
Step-by-step setup
Get running in minutes
We handle the heavy lifting. You provide the data, and we provide the insights.
2. Configure API Key
Add your Valido API key to your `profiles.yml` or as an environment variable. This allows Valido to securely report results to your dashboard.
3. Run & View
Run `dbt seed` and `dbt run`. Valido will automatically ingest your test results. Open the Valido dashboard to see your data quality score and lineage map.
Beyond dbt tests
Continuous validation for modern pipelines
dbt tests are critical, but they are reactive. Valido provides proactive, continuous checks that dbt alone cannot perform.
Continuous Row-Level Checks
Valido sets up background jobs that run every few minutes. It checks for data drift, null percentages, and distribution changes on a per-row basis, flagging issues immediately rather than waiting for the next nightly run.
Intelligent Alert Routing
Instead of flooding your Slack channel with every minor fluctuation, Valido learns your baselines and routes alerts to the right person. If a critical model degrades, the senior engineer is notified; if it's a minor variance, the team is informed.
Configuration
Sample dbt_project.yml
packages:
- package: valido/dbt
version: 1.0.0
# Configure Valido to sync with your warehouse
valido:
api_key: "{{ env_var('VALIDO_API_KEY') }}"
warehouse: "{{ target.name }}"
project_name: "{{ env_var('DBT_PROJECT_NAME') }}"
# Automatically sync dbt tests
sync_dbt_tests: true
# Enable continuous freshness checks
enable_continuous_freshness: true
"Valido has fundamentally changed how we handle data quality."
"Before Valido, we only knew when dbt tests failed. Now we know why and where in the data pipeline the issue originated. The dbt integration saved us a 4-hour incident investigation last week."
— Sarah Jenkins, Lead Data Engineer at FintechGlobal
Connect dbt in 10 minutes
Stop running ad-hoc SQL checks. Start shipping with confidence. Join the data teams using Valido to supercharge their dbt workflows.