Can Workshop replace Looker?

If your main need is governed BI across the whole company, Looker is often a better fit. Workshop is best when you want to build and ship a custom product experience on top of data.

Can I embed Workshop dashboards in another product?

Yes. Workshop is designed for product surfaces and embedding scenarios where UX control matters.

Can Workshop connect to the same warehouses as Looker?

Yes — Workshop can connect to common warehouses and databases, as well as APIs and operational data.

Does Workshop support local development and deployment?

Yes. Workshop is local-first and built for deployment flexibility.

Can I export my Workshop project?

Yes. Workshop emphasizes portability so teams can own what they build.

When should I choose Looker instead?

Choose Looker when governance, semantic modeling, and standardized enterprise reporting are the primary requirements.

Workshop vs Looker

Looker governs metrics. Workshop builds the dashboards and data apps your team actually wants to use.

Try it free. Describe what you want to build.

Our team kept asking for things Looker couldn't do — custom UIs, embedded charts, interactive filters. Workshop reads our LookML layer and builds exactly what they need.

Workshop and Looker both power business intelligence. Workshop builds complete analytics dashboards and data apps with AI, integrating with your existing semantic layer (dbt, LookML). Looker is Google's enterprise BI platform with governed metrics via LookML. Workshop offers faster iteration and full code ownership; Looker provides enterprise-grade governance.

At a Glance

Choose Workshop if you want:

You want to build a custom product experience — not just dashboards.
You need ownership and portability (deploy on your infra, iterate like software).
You want to combine UI, business logic, and AI features into one cohesive app.
You’re embedding analytics inside a larger product and need full UX control.

Choose Looker if you want:

You need enterprise BI with a governed semantic layer and consistent metrics.
Your org prioritizes centralized modeling, definitions, and role-based reporting.
You want embedded analytics built around a BI platform’s governance model.
Your main deliverable is standardized reporting across the organization.

Feature Comparison

	Workshop	Looker
Primary Focus	Product-grade apps	Governed BI + embedded analytics
AI Apps	Yes (in-product AI)	Not primary
Dashboards	Yes (custom UI)	Yes (core)
Hosting Model	Local-first; deploy anywhere	Managed platform
Export / Portability	Exportable, portable projects	Platform-based
Local Development	Yes	No

Where Workshop and Looker Differ

Deployment & Ownership

Workshop: Workshop is built so teams can own their product: local development, flexible deployment, and long-term control over the app lifecycle.

Looker: Looker is a BI platform with strong governance. You get a managed environment and enterprise controls, but your analytics experience is fundamentally tied to the platform.

Working With Real Data

Workshop: Workshop is best when the app *is the product*—a UI that drives workflows, actions, and decisions on top of real data sources.

Looker: Looker is best when your priority is consistent definitions and governed reporting across many teams, supported by a semantic modeling layer.

Flexibility & Tech Stack

Workshop: Workshop lets you design the user experience end-to-end and adapt your tech choices as needs change.

Looker: Looker’s flexibility comes through modeling and governance patterns. It’s powerful for BI, but not designed for full custom application architecture.

Ideal Team Profile

Workshop: Product teams building customer-facing experiences or embedded analytics inside a broader app.

Looker: Data platform and BI teams building a governed analytics layer for an entire organization.

Best for Different Use Cases

Building a Website

Workshop: When Workshop makes sense: You want a real website plus an application experience, shipped as a cohesive product.

Looker: When Looker makes sense: Looker isn’t a website builder; it’s for analytics and reporting.

Building an AI App

Workshop: When Workshop makes sense: AI is a first-class part of your product UX and workflow.

Looker: When Looker makes sense: Your primary need is governed analytics; AI is secondary to BI capabilities.

Building a Dashboard

Workshop: When Workshop makes sense: You need dashboards that are fully custom, interactive, and embedded in a broader product.

Looker: When Looker makes sense: You need standardized reporting, governed metrics, and enterprise analytics patterns.

Building an Internal Tool

Workshop: When Workshop makes sense: You want an internal app with custom workflows and deployment flexibility.

Looker: When Looker makes sense: Your internal need is reporting consistency, not operational tooling.

“We loved Looker for governed reporting, but we needed a real product experience around the data—custom UX, workflows, and ownership. Workshop gave us the flexibility to build that.”
— Director of Data, Enterprise SaaS