# Build Looker Studio Dashboards with BigQuery

BigQuery dashboards can become slow, costly, and hard to govern. This skill helps create Looker Studio data sources, SQL models, filters, layouts, and access controls.

## Install

```bash
npx skillstore add supercent-io/looker-studio-bigquery
```

## Metadata

- Status: approved
- Slug: supercent-io-looker-studio-bigquery
- Skillstore revision: r1
- Version status: missing
- Tree hash: abb33a4f9af6cc8ff415a65c68e377002aa1805a3fc1dd3df5e0802a7cc209fd
- Author: supercent-io
- GitHub username: supercent-io
- License: MIT
- Repository: https://github.com/supercent-io/skills-template/tree/main/.agent-skills/looker-studio-bigquery/
- Ref: f93e9bb0daca99badb6a7e574b97737155d57cb3
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, network, filesystem
- Quality score: 78
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/supercent-io-looker-studio-bigquery
- Manifest: https://skillstore.pages.dev/api/skills/supercent-io-looker-studio-bigquery/manifest

## Capabilities

- Guides BigQuery project, dataset, table, and API setup for Looker Studio.
- Provides SQL patterns for summaries, joins, cohorts, and filtered reports.
- Recommends scheduled queries, partition filters, caching, and chart limits for performance.
- Defines dashboard layouts with KPI tiles, trend charts, tables, maps, and filters.
- Covers BigQuery and Looker Studio access controls, including viewer roles and row-level security.
- Outlines Community Connector configuration using Google Apps Script concepts.

## Use Cases

- Create an executive analytics dashboard: Plan KPIs, charts, filters, and BigQuery summary tables for a business reporting dashboard.
- Improve dashboard performance and cost: Replace slow live queries with partitioned SQL, scheduled summaries, and cache-aware data sources.
- Govern shared reporting access: Map viewer permissions, data source roles, and row-level security for team dashboards.

## Prompt Templates

### Plan a basic dashboard

```
Create a Looker Studio dashboard plan for my BigQuery table. Include KPIs, charts, filters, and required permissions.
```

### Design an optimized data source

```
Review my dashboard data needs and propose BigQuery summary tables, scheduled queries, partitions, and cache settings.
```

### Add filters and governance

```
Design Looker Studio filters, BigQuery roles, and row-level security for a dashboard shared across several teams.
```

### Plan an advanced connector workflow

```
Outline a Community Connector approach for BigQuery reporting, including configuration fields, caching, billing, and security boundaries.
```

## Limitations

- Does not connect to Google Cloud or Looker Studio without user credentials and permissions.
- Does not validate real dataset schemas, billing limits, or organization IAM policies automatically.
- Example SQL uses placeholder project and table names that must be replaced.
- Community Connector guidance is illustrative and not a complete deployable connector.

## Best Practices

- Use scheduled BigQuery summaries for large or repeated dashboard queries.
- Include a date range filter and use partition columns directly.
- Separate dashboard sharing permissions from BigQuery data access permissions.

## Anti Patterns

- Do not connect dashboards directly to very large raw event tables.
- Do not place more than 25 charts on one dashboard page.
- Do not use broad viewer access when row-level controls are required.

## Security Audit

- Audited at: 2026-07-07T04:47:13.572\+00:00
- Summary: The static alerts are false positives caused by Markdown fences, BigQuery identifier backticks, documentation links, and SQL field names. I found no prompt injection, data exfiltration intent, hidden execution, or filesystem abuse in SKILL.md or SKILL.toon.

## Stats

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