creating-looker-dashboard

name	creating-looker-dashboard
description	Looker Developer Onboarding: Step 7 (Final Step). Creates a LookML dashboard in the project, imports it as a user-defined dashboard (UDD) in Looker, and iteratively refines it based on user feedback by syncing changes. Only execute this after Step 6 (Model Setup using `creating-lookml-model`).
license	Apache-2.0
metadata	{"publisher":"google","version":"v1"}

Creating Looker Dashboard & Feedback Loop

This skill guides you through the final step of onboarding: building the target dashboard requested by the user. You will define the dashboard as a LookML dashboard file in the project, import it into Looker as a User-Defined Dashboard (UDD), and iteratively update and synchronize it based on the user's feedback.

Prerequisites

• Looker CLI must be installed and authenticated (Step 2 & 3).
• Looker project, connection, views, and models must be fully set up and validated (Step 4, 5 & 6).

Instructions

1. Retrieve Dashboard Specs & Identify Target Folder

1. Refer back to the target dashboard goal, tables, dimensions, and measures established with the user during the Step 1 (Discovery) interview in the conversation history (and subsequently created in Step 7 (Model)). You must recall these specifications to ensure the dashboard displays the correct data.
2. Locate the target Looker Folder ID to place the dashboard. Since this is a brand-new Looker instance, we will prescriptively place the dashboard in the default Shared folder:
   • List all folders using the Looker CLI: looker-cli folder ls
   • Find the folder named "Shared" in the output. In a brand-new instance, this folder is always present and its ID is almost always "1".
   • Identify the ID of this "Shared" folder and use it as your target folder ID (which will be passed to the folder_id parameter in later steps).

2. Create the LookML Dashboard File (CLI)

You must define the dashboard structure as a LookML dashboard file in your project:

1. Create the dashboards directory: If the dashboards/ directory does not yet exist in the project, create it using the Looker CLI:

   looker-cli project directory create {project_id} dashboards
   

2. Generate Dashboard LookML: Write the LookML dashboard definition locally (e.g. to /tmp/{dashboard_name}.dashboard.lookml). Ensure the file uses the .dashboard.lookml extension.

3. Upload the Dashboard File: Upload the file to your Looker project dashboards folder (path convention dashboards/{dashboard_name}.dashboard.lookml):

   looker-cli project file create {project_id} dashboards/{dashboard_name}.dashboard.lookml /tmp/{dashboard_name}.dashboard.lookml
   

4. Critical Inclusion Step: You MUST include the dashboard files in your LookML model file ({model_name}.model.lkml) so they can be discovered by the project validator and the CLI import/sync commands:

   include: "/dashboards/**/*.dashboard.lookml"
   

5. Inside the dashboard file, write the LookML dashboard definition, configuring tiles (elements) that display the dimensions and measures you created in Step 7. It is highly recommended to use layout: newspaper (which supports grid coordinates row, col, width, and height out of 24 columns) to prevent import errors that can happen with older layout: grid row groupings.

Example Dashboard LookML (layout: newspaper):

- dashboard: sales_performance
  title: Sales Performance Overview
  layout: newspaper
  preferred_viewer: dashboards-next

  elements:
    - name: total_revenue_tile
      title: Total Revenue Over Time
      model: ecommerce
      explore: orders
      type: looker_line
      fields: [orders.created_date, orders.total_revenue]
      sorts: [orders.created_date desc]
      limit: 500
      row: 0
      col: 0
      width: 12
      height: 8

    - name: order_count_tile
      title: Top Countries by Orders
      model: ecommerce
      explore: orders
      type: looker_column
      fields: [users.country, orders.count]
      sorts: [orders.count desc]
      limit: 10
      row: 0
      col: 12
      width: 12
      height: 8

Note: Make sure the model and explore properties on each tile match the model and explore names defined in your project, and the fields use fully qualified view_name.field_name formats.

3. Validate and Commit LookML

Validate the project to ensure the dashboard syntax is perfect and has no reference errors:

looker-cli api project validate_project {project_id}

If errors are returned, fix the LookML dashboard definition and re-validate until clean.

4. Import LookML Dashboard as UDD (CLI)

Import the LookML dashboard into your target Folder as a User-Defined Dashboard (UDD). This converts it from a static file into a database-backed dashboard in Looker.

1. Construct the lookml_dashboard_id in the format {model_name}::{dashboard_name} (e.g. ecommerce::sales_performance).

2. Ensure Dev Mode Workspace Context: By default, Looker CLI sessions execute in the production workspace. Since your newly created dashboard exists only in Development Mode, you MUST switch the CLI session to the dev workspace immediately prior to importing/syncing. Chain the session update command to the import command:

   looker-cli session update dev && looker-cli dashboard import lookml {model_name}::{dashboard_name} {folder_id}
   

3. The command will return a JSON object containing the details of the imported UDD. Record the dashboard numeric id (e.g., 45) or slug from the response.

5. Validate Dashboard Content (SQL Query Verification Check)

Looker's project validation only checks LookML syntax—it does not verify if the SQL queries for each tile execute successfully against the database. To guarantee that the dashboard is 100% free of query errors before presenting it to the user, you MUST retrieve and execute the query behind every single dashboard tile:

1. Retrieve the dashboard element details (specifically targeting query_id) for your newly imported UDD dashboard:

   looker-cli dashboard cat {udd_id} --fields "dashboard_elements(query_id)"
   

2. For each unique query_id returned in the JSON results (excluding any null values from text tiles), execute the query to verify database correctness:

   looker-cli query runquery {query_id}
   

3. Verify that each query executes successfully and returns data without SQL or database errors. If any query fails (indicating a database column mismatch, bad SQL dialect function, or GCP permission issue), you MUST resolve the issue in your LookML views, commit the changes, re-run looker-cli api project validate_project {project_id}, synchronize using looker-cli dashboard sync lookml, and re-verify using this sequence until all queries execute successfully.

6. Present and Iterate with User (Interactive Step)

1. Present the imported dashboard link to the user: {instance_url}/dashboards/{udd_id} (or /dashboards-next/{udd_id}).

2. STOP AND ASK the user for feedback on the layout, chart types, or labels:

   "I have successfully built and imported your new dashboard! You can view it here: {dashboard_url}

   Does this look good to you? Let me know if you'd like me to change any chart types, add new metrics, or adjust the layout!"

3. STOP AND WAIT for the user's response. Do not call any tools.

7. Refine and Synchronize Changes

If the user requests changes to the dashboard (e.g., "make the order count a bar chart instead of column," or "add a filter"):

1. Edit your local LookML dashboard file and update it on the Looker server:

   looker-cli project file update {project_id} dashboards/{dashboard_name}.dashboard.lookml /tmp/{dashboard_name}.dashboard.lookml
   

2. Validate the project:

   looker-cli api project validate_project {project_id}
   

3. Propagate your changes directly to the imported UDD dashboard using the CLI sync command:

   looker-cli dashboard sync lookml {model_name}::{dashboard_name}
   

4. Re-run Query Validation: Run the query verification check again to ensure your refinements did not introduce any new SQL or database errors:

   • Fetch the UDD elements again (to capture any new tile queries): looker dashboard cat {udd_id} --fields "dashboard_elements(query_id)"
   • For each returned query_id, run the query to verify SQL correctness: looker-cli query runquery {query_id}

5. Ask the user to refresh their browser and review the changes. Repeat this loop until the user is fully satisfied!