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What you can achieve after this docs path

If you are new to Looky, this docs set takes you from zero to a published workspace with at least one dashboard visible in https://my.looky.studio. It is written for builders, analytics engineers, and delivery leads who need repeatable execution, not theory.

Getting Started

Access and first success

Invitation, sign-in, CLI linkage, billing context, BigQuery setup, first workspace.

Build Workflow

Author and publish content

Sources, models, cache, visualizations, dashboards, exports, validation, push.

Reference

Command and failure playbook

Fast lookup for CLI commands and concrete troubleshooting sequences.

Build focused answers, not giant dashboards

Most BI tools push you toward one dashboard that tries to answer everything. The result is something nobody reads. Looky is built around the opposite: one focused dashboard per business question.

A dashboard that answers "Where is fulfillment leaking this month?" is something a team will open every morning. A dashboard with 40 charts and no clear question is a loading screen.

This shapes everything in the build workflow:

  • Models define your semantic layer once. One measure definition, reused across every chart that needs it.
  • Visualizations bind one query to one chart. No logic, no duplication.
  • Dashboards compose visualizations around a single question — small enough that the answer is obvious, specific enough to be actionable.
  • Document mode takes that focused dashboard and makes it a deliverable: a top-to-bottom report that exports to PDF on a schedule and lands in the right hands without anyone having to open the UI.
  • Cross-filtering in interactive dashboards lets users click any bar or point to slice all charts simultaneously — the kind of exploration that surfaces answers that no single chart could show alone.

The ecommerce-showcase workspace demonstrates this throughout: four separate dashboards, each answering one distinct question about the business.

Zero-to-dashboard path (45 to 90 minutes)

  1. Accept invitation and verify role scope in the UI (Owner Invitation).
  2. Sign in to https://my.looky.studio and link CLI to your local root (Sign In and Connect the CLI).
  3. Set up BigQuery service account and wire credentials into workspace runtime config (BigQuery Dataset Access).
  4. Set billing context and either pull ecommerce-showcase or create a new workspace skeleton (Create Your First Workspace).
  5. Author sources, models, visualizations, and dashboards (Build Workflow).
  6. Run looky validate, looky diff, looky push and verify in UI.

Command sequence most teams run daily

looky login https://my.looky.studio <local_root>
looky whoami

cd <local_root>
looky billing list
looky billing use <billing_account_id>

cd <local_root>/<billing_account_id>
looky pull ecommerce-showcase

cd ecommerce-showcase
looky status
looky validate
looky diff
looky push
looky list visualizations
looky list dashboards

Placeholder convention: <local_root> is your machine root linked to the instance, <billing_account_id> is your active billing account, and <workspace_slug> is one workspace folder under that billing account.

What makes this docs set different

  • Every phase includes success criteria, not only command examples.
  • The workflow is end-to-end: access, BigQuery setup, authoring, publish, verify.
  • Examples are grounded in a real workspace structure and real CLI commands taken from the ecommerce-showcase.
  • Troubleshooting is organized by symptom with deterministic fix steps.