Secoda Docs
Get Started
  • Getting Started with Secoda
    • Secoda as an Admin
      • Deployment options
      • Sign in options
      • Settings
      • Connect your data
        • Define Service Accounts
        • Choose which schemas to extract
      • Customize the workspace
      • Populate Questions with FAQs
      • Invite your teammates
        • Joining & Navigating between Multiple Workspaces
      • Onboard new users
        • Onboarding email templates
        • Onboarding Homepage template
        • Training session guide
      • User engagement and adoption
        • Tips & Tricks to share with new users
    • Secoda as an Editor
    • Secoda as a Viewer
      • Introduction guide
      • Requesting changes in Secoda
  • Best practices
    • Setting up your workspace
    • Integrating Secoda into existing workflows
    • Documentation best practices
    • Glossary best practices
    • Data governance
    • Data quality
    • Clean up your data
    • Tool migrations using Secoda
    • Slack <> Questions workflow
    • Defining resources workflow
    • Streamline data access: Private and public teams workflow
    • Exposing Secoda to external clients
  • Resource Management
    • Editing Properties
      • AI Description Editor
      • Bulk Editing
      • Propagation
      • Templates
    • Resource Sidesheet
    • Assigning Owners
    • Custom Properties
    • Tags
      • Custom Tags
      • PII Identifier
      • Verified Identifier
    • Import and Export Resources
    • Related Resources
  • User Management
    • Roles
    • Teams
    • Groups
  • Integrations
    • Integration Settings
    • Data Warehouses
      • BigQuery
        • BigQuery Metadata Extracted
      • Databricks
        • Databricks Metadata Extracted
      • Redshift
        • Redshift Metadata Extracted
      • Snowflake
        • Snowflake Metadata Extracted
        • Snowflake Costs
        • Snowflake Native App
      • Apache Hive
        • Apache Hive Metadata Extracted
      • Azure Synapse
        • Azure Synapse Metadata Extracted
      • MotherDuck
        • MotherDuck Metadata Extracted
      • ClickHouse
        • ClickHouse Metadata Extracted
    • Databases
      • Druid
        • Druid Metadata Extracted
      • MySQL
        • MySQL Metadata Extracted
      • Microsoft SQL Server
        • Page
        • Microsoft SQL Server Metadata Extracted
      • Oracle
        • Oracle Metadata Extracted
      • Salesforce
        • Salesforce Metadata Extracted
      • Postgres
        • Postgres Metadata Extracted
      • MongoDB
        • MongoDB Metadata Extracted
      • Azure Cosmos DB
        • Azure Cosmos DB Metadata Extracted
      • SingleStore
        • SingleStore Metadata Extracted
      • DynamoDB
        • DynamoDB Metadata Extracted
    • Data Visualization Tools
      • Amplitude
        • Amplitude Metadata Extracted
      • Looker
        • Looker Metadata Extracted
      • Looker Studio
        • Looker Studio Metadata Extracted
      • Metabase
        • Metabase Metadata Extracted
      • Mixpanel
        • Mixpanel Metadata Extracted
      • Mode
        • Mode Metadata Extracted
      • Power BI
        • Power BI Metadata Extracted
      • QuickSight
        • QuickSight Metadata Extracted
      • Retool
        • Retool Metadata Extracted
      • Redash
        • Redash Metadata Extracted
      • Sigma
        • Sigma Metadata Extracted
      • Tableau
        • Tableau Metadata Extracted
      • ThoughtSpot
        • ThoughtSpot Metadata Extracted
      • Cluvio
        • Cluvio Metadata Extracted
      • Hashboard
        • Hashboard Metadata Extracted
      • Lightdash
        • Lightdash Metadata Extracted
      • Preset
        • Preset Metadata Extracted
      • Superset
        • Superset Metadata Extracted
      • SQL Server Reporting Services
        • SQL Server Reporting Services Metadata Extracted
      • Hex
        • Hex Metadata Extracted
      • Omni
        • Omni Metadata Extracted
    • Data Pipeline Tools
      • Census
        • Census Metadata Extracted
      • Stitch
        • Stitch Metadata Extracted
      • Airflow
        • Airflow Metadata Extracted
      • Dagster
        • Dagster Metadata Extracted
      • Fivetran
        • Fivetran Metadata Extracted
      • Glue
        • Glue Metadata Extracted
      • Hightouch
        • Hightouch Metadata Extracted
      • Apache Kafka
        • Apache Kafka Metadata Extracted
      • Confluent Cloud
        • Confluent Cloud Metadata Extracted
      • Polytomic
        • Polytomic Metadata Extracted
      • Matillion
        • Matillion Metadata Extracted
      • Airbyte
        • Airbyte Extracted Metadata
      • Informatica
        • Informatica Metadata Extracted
      • Azure Data Factory
        • Azure Data Factory Metadata Extracted
    • Data Transformation Tools
      • dbt
        • dbt Cloud
          • dbt Cloud Metadata Extracted
        • dbt Core
          • dbt Core Metadata Extracted
      • Coalesce
        • Coalesce Metadata Extracted
    • Data Quality Tools
      • Cyera
      • Dataplex
        • Dataplex Metadata Extracted
      • Great Expectations
        • Great Expectations Metadata Extracted
      • Monte Carlo
        • Monte Carlo Metadata Extracted
      • Soda
        • Soda Metadata Extracted
    • Data Lakes
      • Google Cloud Storage
        • GCS Metadata Extracted
      • AWS S3
        • S3 Metadata Extracted
    • Query Engines
      • Trino
        • Trino Metadata Extracted
    • Custom Integrations
      • File Upload
        • CSV File Format
        • JSONL File Format
        • Maintain your Resources
      • Marketplace
        • Secoda SDK
        • Upload and Connect your Marketplace Integration
        • Publish the Integration
        • Example Integrations
      • Secoda Fields Explained
    • Security
      • Connecting via Reverse SSH Tunnel
      • Connecting via SSH Tunnel
      • Connecting via VPC Peering
      • Connecting via AWS Cross Account Role
      • Connecting via AWS PrivateLink
        • Snowflake via AWS PrivateLink
        • AWS Service via AWS PrivateLink
      • Recommendations to Improve SSH Tunnel Concurrency on SSH Bastion
    • Push Metadata to Source
  • Extensions
    • Chrome
    • Confluence
      • Confluence Metadata Extracted
      • Confluence best practices
    • Git
    • GitHub
    • Jira
      • Jira Metadata Extracted
    • Linear
    • Microsoft Teams
    • PagerDuty
    • Slack
      • Slack user guide
  • Features
    • Access Requests
    • Activity Log
    • Analytics
    • Announcements
    • Audit Log
    • Automations
      • Automations Use Cases
    • Archive
    • Bookmarks
    • Catalog
    • Collections
    • Column Profiling
    • Data Previews
    • Data Quality Score
    • Documents
      • Comments
      • Embeddings
    • Filters
    • Glossary
    • Homepage
    • Inbox
    • Lineage
      • Manual Lineage
    • Metrics
    • Monitors
      • Monitoring Use Cases
    • Notifications
    • Policies
    • Popularity
    • Publishing
    • Queries
      • Query Blocks
        • Chart Blocks
      • Extracted Queries
    • Questions
    • Search
    • Secoda AI
      • Secoda AI User Guide
      • Secoda AI Use Cases
      • Secoda AI Security FAQs
      • Secoda MCP Server
    • Sharing
    • Views
  • Enterprise
    • SAML
      • Okta SAML
      • OneLogin SAML
      • Microsoft Azure AD SAML
      • Google SAML
      • SCIM
      • SAML Attributes
    • Self-Hosted
      • Additional Resources
        • Additional Environment Variables
          • PowerBI OAuth Application (on-premise)
          • Google OAuth Application (on-premise)
          • Github Application (on-premise)
          • OpenAI API Key Creation (on-premise)
          • AWS Bucket with Access Keys (on-premise)
        • TLS/SSL (Docker compose)
        • Automatic Updates (Docker compose)
        • Backups (Docker compose)
        • Outbound Connections
      • Self-Hosted Changelog
    • SIEM
      • Google Chronicle
  • API
    • Get Started
    • Authentication
    • Example Workflows
    • API Reference
      • Getting Started
      • Helpful Information
      • Audit Logs
      • Charts
      • Collections
      • Columns
      • Custom Properties
      • Dashboards
      • Databases
      • Documents
      • Events
      • Groups
      • Integrations
      • Lineage
      • Monitors
      • Resources
      • Schemas
      • Tables
      • Tags
      • Teams
      • Users
      • Questions
      • Queries
      • Getting Started
      • Helpful Information
      • Audit Logs
      • Charts
      • Collections
      • Columns
      • Custom Properties
      • Dashboards
      • Databases
      • Documents
      • Events
      • Groups
      • Integrations
      • Lineage
      • Monitors
      • Resources
      • Schemas
      • Tables
      • Tags
      • Teams
      • Users
      • Questions
      • Queries
  • FAQ
  • Policies
    • Terms of Use
    • Secoda AI Terms
    • Master Subscription Agreement
    • Privacy Policy
    • Security Policy
    • Accessibility Statement
    • Data Processing Agreement
    • Subprocessors
    • Service Level Agreement
    • Bug Bounty Program
  • System Status
  • Changelog
Powered by GitBook
On this page
  • How dbt metadata appears in Secoda
  • Syncing metadata back to dbt

Was this helpful?

  1. Integrations
  2. Data Transformation Tools

dbt

An overview of the dbt integrations with Secoda

Last updated 5 months ago

Was this helpful?

Secoda integrates seamlessly with both dbt Cloud and dbt Core, enhancing your ability to manage and visualize data transformations and dependencies within your workspace. This guide details the integration process, the display of dbt metadata in Secoda, and how to utilize dbt features effectively.

You can learn more about the integration setup by clicking into the linked documents.

dbt is a secondary integration that adds additional metadata on to your data warehouse or relational database tables. Before connecting dbt make sure to connect a data warehouse or relational database first. These include Snowflake, BigQuery, Postgres, Redshift, etc.

How dbt metadata appears in Secoda

Once the integration is established:

  • If connected, Jobs will appear in the Catalog which you can click into to see Test results and additional metadata for those Tests.

  • Data warehouse or relational database tables associated with dbt will display a dbt icon next to their titles.

  • A 'Tests' tab will appear for resources where dbt Tests have been run.

  • You can view dbt metadata overlaid on the lineage graphs to understand dependencies and transformations better.

  • Within the lineage tab, lineage nodes will feature a checkmark icon. Clicking on these icons reveals which dbt Tests have been run and their statuses.

  • See the video below of what a correctly functioning integration should look like:

This integration empowers teams to track and verify data transformations directly within the Secoda environment, ensuring transparency and accuracy in data operations. Whether you use dbt Core or dbt Cloud, Secoda facilitates a comprehensive view of your data landscape.

Syncing metadata back to dbt

You can seamlessly sync metadata updates from Secoda directly back to your dbt models. This streamlines workflows and enhances data governance by ensuring that your dbt models stay synced with the latest metadata in Secoda.

Here's how you can set it up:

  1. Set up a GitHub Integration: Connect your GitHub account to enable syncing between Secoda and your code repository.

  2. Initiate a Metadata Push: Trigger a metadata push via the GitHub sync history tab within Secoda. This process is straightforward and integrates directly with your workflow.

  3. Automatic Pull Request Generation: Once a metadata push is initiated, a Pull Request is automatically created in GitHub. This PR includes updates for column and table descriptions, owner details, and tags, ensuring that your dbt models are always up-to-date.

Benefits:

  • Keeps your dbt models consistently updated with the latest metadata from Secoda.

  • Enhances collaboration by ensuring all team members work with the most current data definitions.

  • Reduces manual errors by automating the sync process.