Looker Connector | Integrate BI with Collate Docs

• Requirements
• Metadata Ingestion
• Entity Mapping
• Lineage
• Troubleshooting

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Requirements

• Dashboards & Charts
• LookML Models For the project metadata being ingested:
• The actual LookML Project an Explore or View is developed in.
• For Dashboards, the folder name from the UI, since there is no other hierarchy involved there. In terms of permissions, a user with access to the Dashboards and LookML Explores to be ingested is required. Create your API credentials by following Looker API authentication. However, LookML Views are not present in the Looker SDK. Instead, that information must be extracted directly from the GitHub repository holding the source .lkml files. To get this metadata, a GitHub token with read only access to the repository is required. For steps, see Creating a personal access token.

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Entity Mapping

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Example Structure

Folder: Sales Team
└── Dashboard: Revenue Overview
    ├── Tile: Monthly Revenue
    └── Tile: Regional Breakdown
LookML Project: sales_analytics
├── Explore: revenue
└── View: orders

Dashboard: "Revenue Overview" (Project: "Sales Team")
├── Chart: "Monthly Revenue"
└── Chart: "Regional Breakdown"
Data Model: "revenue" (Project: "sales_analytics")
Data Model: "orders" (Project: "sales_analytics")

• Looker dashboards appear as Collate dashboards, organized by their Looker folder
• Dashboard tiles appear as charts underneath their dashboard
• LookML Explores and Views appear as data models, organized by their LookML project
• The project field is sourced differently depending on entity type: a Looker folder for Dashboards, a LookML project for Data Models

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Metadata Ingestion

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Step 1: Add New Service

1. Navigate to Settings > Services and select Dashboard Services.
2. Click Add New Service.

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Step 2: Select a Service and Connector

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Step 3: Add Service Name and Description

• Enter a unique, descriptive Service Name. Collate identifies services by their service name. Enter a name that distinguishes this deployment from other Looker services you are ingesting metadata from.
• Optional: Enter a Description for the service.

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Step 4: Configure Connection Options

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Select Ingestion Runner

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Enter Connection Details

• Client ID: User’s Client ID to authenticate to the SDK. This user should have privileges to read all the metadata in Looker.
• Host and Port: URL to the Looker instance, for example, https://my-company.region.looker.com.

• Client Secret: User’s Client Secret for the same ID provided.

• Git Credentials: Choose how to extract the .lkml files that hold your LookML views and their lineage to source tables:
  • No Git Credentials: Default option. Skips LookML view ingestion and lineage to source tables.
  • Local Path: Path to the repository on the local file system where the ingestion pipeline runs, for example /opt/looker/repo.
  • GitHub Credentials: Credentials for a GitHub repository.
    • Git Host URL: GitHub instance URL. For GitHub.com, use https://github.com.
    • Repository Owner: The owner (user or organization) of a GitHub repository. For example, in https://github.com/open-metadata/OpenMetadata, the owner is open-metadata.
    • Repository Name: The name of a GitHub repository. For example, in https://github.com/open-metadata/OpenMetadata, the name is OpenMetadata. To ingest LookML files from multiple repositories under the same owner, provide a comma-separated list, for example looker-main-repo,looker-secondary-repo,looker-analytics-repo.
    • API Token: Token to use the API. This is required for private repositories and to avoid hitting API rate limits.
    To create a fine-grained personal access token, see Creating a fine-grained personal access token. When configuring, give repository access to Only select repositories and choose the one containing your LookML files. Set Repository Permissions to Read-only for Contents.
  • BitBucket Credentials: Credentials for a BitBucket repository.
    • Git Host URL: BitBucket instance URL. For BitBucket Cloud, use https://bitbucket.org.
    • Repository Owner: The owner (user or organization) of the repository.
    • Repository Name: The name of the repository. To ingest LookML files from multiple repositories under the same owner, provide a comma-separated list, for example looker-main-repo,looker-secondary-repo,looker-analytics-repo.
    • API Token: Token to use the API. This is required for private repositories and to avoid hitting API rate limits.
    • Main Branch: Main production branch of the repository, for example main. This field is required.
  • GitLab Credentials: Credentials for a GitLab repository.
    • Git Host URL: GitLab instance URL. For GitLab.com, use https://gitlab.com.
    • Repository Owner: The owner (user or organization) of the repository.
    • Repository Name: The name of the repository. To ingest LookML files from multiple repositories under the same owner, provide a comma-separated list, for example looker-main-repo,looker-secondary-repo,looker-analytics-repo.
    • API Token: Token to use the API. This is required for private repositories and to avoid hitting API rate limits.

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Test Connection

1. Click Test Connection to verify the credentials.
2. After the test succeeds, click Save.

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Step 5: Configure Ingestion Options

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How Filter Patterns Work

• Include: Add one or more comma-separated values. Each value uses one of the following match types. Collate ingests only assets whose names match at least one rule. Leave blank to include all assets.
• Exclude: Add one or more comma-separated values. Each value uses one of the following match types. Collate skips any asset whose name matches a rule. Leave blank to exclude nothing.

• contains: matches any name containing the value. For example, sales matches my_sales_data and sales_2024.
• starts with: matches names beginning with the value. For example, prod_ matches prod_db and prod_schema.
• ends with: matches names ending with the value. For example, _raw matches events_raw and logs_raw.
• is exactly: matches the exact name only. For example, analytics matches only analytics.
• matches regex: matches names using a regular expression. For example, ^prod_.*_v\d+$ matches prod_events_v1.

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Filter Options

• Dashboard: Controls which dashboards Collate ingests from the source.
• Chart: Controls which charts within the ingested dashboards are included.

• Scan Mode: Choose between the following scan modes:
  • Scan all: Ingests every asset of that type the connector can access. This is the default.
  • Only specific: Enables include rules so only assets matching at least one rule are ingested.
• Exclude system toggle: Use this toggle to filter out system-reserved names defined by the connector for that asset type.
• Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
• Preview: Shows a real-time summary of what will be in scope based on your current rules.
• Include rules: In Only specific mode, click + Add to define a rule. Added rules appear as chips. An asset is included if it matches any rule.

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Step 6: Create & Deploy

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Configure Metadata Agent and Schedule Ingestion

1. Navigate to Settings > Services and select the Dashboards service.
2. Select your service and click the Agents tab.
3. Click Add Agent and select Metadata from the dropdown. For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
4. On the Configure Ingestion page, do the following and click Next.
   • Name this Ingestion: Enter a unique, recognizable name for this ingestion pipeline.
   • Agent Setup: Configure ingestion parameters. The following fields are available:

     Field	Default	Description
     Db Service Prefixes	—	List of database service name prefixes used to resolve lineage between dashboards and database assets. Accepted formats: DBService, DBService.Database, DBService.Database.Schema, DBService.Database.Schema.Table.
     Query Parser Type	Auto	Select the SQL parser used for lineage extraction from dashboard queries. Auto selects the best available parser automatically. SqlGlot is a high-performance parser with excellent dialect support; falls back to SqlParse on failure. SqlFluff is a comprehensive parser with strong dialect support; falls back to SqlParse on failure.
     Mark Deleted Dashboards	On	Soft-delete dashboards in Collate when they are removed from the source. Associated lineage is also deleted.
     Mark Deleted Data Models	On	Soft-delete data models in Collate when they are removed from the source. Associated lineage is also deleted.
     Mark Deleted Charts	On	Soft-delete charts in Collate when they are removed from the source.
     Include Data Models	On	Ingest data model metadata.
     Include Draft Dashboards	On	Ingest dashboards that are in draft state.
     Include Usage	On	Collect and ingest usage statistics for dashboards.

     
   • Filter Patterns: Apply include or exclude rules to scope which dashboards, charts, data models, and projects this agent ingests. These follow the same filter options described in Step 5.
   • Scope & Behaviour: Control what metadata to include and how to handle deletions. Toggle each option on or off based on your needs:

     Toggle	Default	Description
     Enable Debug Log	Off	Sets the ingestion log level to DEBUG. Useful for troubleshooting.
     Include Current Owners	Off	When enabled, replaces the current owner with a new owner from the source if the current owner is null. Recommended to keep enabled during the first metadata ingestion to capture owner information.
     Include Tags	On	Ingest tags from the source.
     Override Metadata	Off	When on, source values overwrite existing descriptions, tags, owners, and display names in Collate. When off, Collate only updates fields that have no existing value.
     Override Lineage	Off	When on, existing lineage is replaced with newly extracted lineage on each run.

     
5. On the Schedule Interval page, set when the agent runs:
   • Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
   • On-Demand: No automatic schedule. Trigger the agent manually when needed.
   
6. Click Add to deploy the agent.

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Lineage

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Lineage

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How to Set Up Lineage

1. Go to Settings > Services > Dashboards.
2. Click the dashboard service you’ve added.
3. Go to the Agents tab, then select Add Agent > Add Metadata Agent. If a metadata agent already exists, select the three-dot context menu (⋮) next to it and select Edit.
4. In the Configure Ingestion step, scroll down to the Lineage Information section.
5. Optionally enter one or more database service names in the Db Service Prefixes field to restrict table matching to specific services. If left blank, Collate searches across all ingested database services.

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Troubleshooting