Looker AI Dashboard Builder
Reasons Teams Switch
NLQ for Looker
Type “Show ARR growth by segment vs target” and get a chart plus the underlying LookML query instantly.Insight summaries
Each dashboard tile can display AI-written callouts that explain spikes, dips, or anomalies in everyday language.Auto-model suggestions
Connect a warehouse and the builder proposes join paths, time grains, and calculated fields so you skip schema guesswork.Alert studio
Set natural-language rules like “Ping RevOps if churn probability exceeds 3%” and deliver via email, Slack, or webhook.Embedded governance
Reuse LookML permissions, data governing layers, and audit trails to keep analysts and AI outputs on the same rulebook.One-click sharing
Publish dashboards to secure links or embed in internal tools with automatic row-level security.Dashboard Design Tips
1. Write decision-first prompts
Before building, write the question decision-makers need answered (“Should we expand paid spend?”) and keep visuals laser-focused on it.
2. Align to a metric tree
Group tiles according to how metrics roll up—north star, contributing inputs, diagnostic slices—so execs can scan logically.
3. Limit palette drift
Stick to two accent colors plus neutrals; AI theming in Looker can enforce your brand hex codes automatically.
4. Document assumptions
Use the narrative sidebar to note data latency, filters, or modeling caveats—future viewers will thank you.
5. Pair visuals with text
Every complex chart should include a short AI-generated insight explaining “so what” in one sentence.
6. Set alert hygiene
Review alert rules quarterly so teams don’t get numb to noisy notifications.
Who Uses It
RevOps analysts
Translate GTM questions into dashboards without hunting for SQL snippets.
Product leaders
Monitor activation, feature adoption, and health scores with anomaly callouts.
Finance teams
Build forward-looking KPIs and variance explanations straight from the warehouse.
Data PMs
Prototype Looker explores faster, get stakeholder feedback, then harden the model.