Looker BI from the IDE

BuildNew

First production dashboard delivered in 48-72 hours

CRM schema discovery to production Looker dashboards — without leaving your IDE. Spec-first provisioning, iterative editing, and programmatic automation replace the traditional multi-month, multi-role BI project.

Timelines are engagement estimates including discovery, pipeline setup, data modeling, and stakeholder review. The CLI itself provisions dashboards in seconds.

The Problem

Starting from scratch

Standing up BI from zero requires data engineers for pipelines, analytics engineers for modeling, and BI developers for dashboards. Three roles working sequentially. Months to first dashboard. Every change goes through the same slow cycle.

Already have Looker

Even orgs with existing Looker instances spend weeks on every new dashboard. Manual tile layout in the GUI, no version control on dashboard definitions, no dry-run preview, changes coupled to a BI admin's calendar.

The Prompt

Paste this into Claude Code with g-gremlin available.

We need production dashboards for the RevOps team:
- Renewals pipeline by stage and month
- Net retention by cohort
- Forecast vs. quota with stage progression
- Churn analysis by segment and tenure

Data lives in Salesforce. We have Looker in-house. Build the full pipeline and provision the dashboards.

Spec-First Dashboard Provisioning

Dashboards are defined as version-controlled YAML specs — tiles, filters, layout, drill-throughs. The CLI applies these specs through Looker's programmatic API with deterministic upsert logic. --dry-run previews mutations before writing. Merge mode adds without touching unmanaged elements. Replace mode requires explicit --force.

How It Works

Discover Schema

Connect to Salesforce and map objects, fields, relationships, and picklist values.

Build Data Pipeline

Extract from CRM and load into BigQuery with incremental refresh schedules.

Model Analytics Layer

Write SQL transformations: staging, business logic, and metric definitions.

Define Semantic Layer

Generate LookML models with dimensions, measures, explores, and join logic.

Provision Dashboards

Apply YAML specs through Looker API: tiles, filters, layout, drill-throughs.

Iterate in Minutes

Add tiles, modify filters, refine layout — all from the IDE.

After you paste this prompt, Claude Code:

"RevOps needs a renewals dashboard in Looker. Let me verify the Looker connection and discover the Salesforce schema."

Running

$ g-gremlin looker doctor --json

Connection: OK | Instance: client.cloud.looker.com | API: 4.0 | Permissions: admin

Running

$ g-gremlin sfdc describe --sobject Opportunity --fields-only

52 fields mapped. Key: StageName, Amount, CloseDate, OwnerId, ForecastCategory

Running

$ g-gremlin looker describe models --json

Models: analytics (6 explores), marketing (3 explores)

Running

$ g-gremlin looker describe explores --model analytics --json

Explores: renewals, pipeline, retention, forecast, accounts, opportunities

"Schema mapped, Looker connected, analytics model ready. Provisioning renewals dashboard from YAML spec."

Running

$ g-gremlin looker dashboard create --spec config/bi/looker/renewals.dashboard.yaml --dry-run --json

[Dry run] Would create "Renewals Pipeline" in space 123 3 tiles: Monthly Renewal ARR (column), Renewed ARR (single_value), At-Risk (table) 2 filters: fiscal_quarter, owner Mode: merge | No changes written

Running

$ g-gremlin looker dashboard create --spec config/bi/looker/renewals.dashboard.yaml --json

Dashboard created: id=456 "Renewals Pipeline" 3 tiles created | 2 filters applied URL: https://client.cloud.looker.com/dashboards/456

Running

$ g-gremlin looker dashboard add-filter --dashboard-id 456 --spec fiscal_year.yaml --json

Filter added: fiscal_year | Dashboard 456 now has 3 filters

Renewals dashboard live in Looker. 3 tiles, 3 filters. Next: provision remaining 5 dashboards from specs.

Key Capabilities

Progressive Introspection

Discover models, explores, dimensions, and measures. No context-switching to a separate BI tool.

Inline Queries

Run ad-hoc queries against any explore. Output CSV or JSON for validation before building dashboards.

Spec-First Provisioning

Define dashboards as version-controlled YAML specs. Deterministic upsert with --dry-run preview.

Iterative Editing

Add or remove individual tiles and filters on live dashboards. No full redeploy required.

Round-Trip Workflow

Describe an existing dashboard, edit the output, redeploy. No manual format translation.

Safe Mutation Controls

Merge mode preserves unmanaged elements. Replace mode requires explicit --force. Dry-run on everything.

Engagement Timeline

Milestone 1 — One Working Dashboard

48-72 hours

Connect to Salesforce and map the relevant schema
Stand up the data pipeline (CRM to BigQuery)
Build the analytics layer for one domain
Deliver one complete, interactive dashboard in Looker

Milestone 2 — Full Dashboard Suite

2-3 weeks

Expand to remaining dashboards
Add LookML validation and metric regression checks
Document the change workflow for ongoing iteration
Stakeholder review and polish rounds

These are engagement timelines including discovery, pipeline setup, data modeling, and stakeholder review. The CLI provisions dashboards in seconds.

Works With Your Existing Stack

CRM Sources

Salesforce, HubSpot, Dynamics 365, or any CRM with API access. g-gremlin handles schema discovery and data extraction.

Data Warehouse

BigQuery as Looker's data source. Data lands in BigQuery via Google's Data Transfer Service or g-gremlin's sink commands.

Visualization

Looker (full Looker with LookML, not Looker Studio). g-gremlin provisions dashboards via Looker's programmatic API.

By the Numbers

48-72 hrs

First dashboard delivered

2-3 weeks

Full dashboard suite

3-6 months

Traditional approach

Not required

Dedicated BI team

Note: Timelines are engagement estimates. Someone still writes YAML specs, defines the data model, and reviews dashboards. The tooling eliminates the dedicated Looker admin role and collapses the analytics engineer + dashboard builder into one workflow.

Full Documentation

Looker Quickstart Guide

Setup, authentication, and your first dashboard

CLI Command Reference

Complete reference for all Looker commands

See It Before You Commit

One working dashboard in your Looker instance. No long-term commitment. No new vendors.

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