Looker
What it is: Google Cloud's BI platform. LookML modeling language defines metrics once, use everywhere.
What It Does Best
Single source of truth. Define "revenue" once in LookML. Everyone gets the same number.
Version control. Git for your metrics. Code review for analytics logic. See who changed what.
Embedded analytics. Put dashboards in your product. White-label for customers.
Key Features
LookML: Code-based modeling language for metrics and dimensions
Git integration: Version control for analytics logic
Embedded dashboards: White-label analytics in your product
BigQuery integration: Native Google Cloud data warehouse support
API-first: Programmatic access to all features
Pricing
Contact sales. Typically $3,000+/month for small teams
Enterprise: Custom pricing based on users and features
When to Use It
✅ Data team writes code
✅ Need metric governance
✅ On Google Cloud
✅ Want embedded analytics
✅ Metric inconsistency is a major problem
When NOT to Use It
❌ Small budget (Power BI 10x cheaper)
❌ Business users who don't code
❌ Not on Google Cloud (integrations limited)
❌ Small team without data engineers
❌ Need quick setup (steep learning curve)
Common Use Cases
Product analytics: Embed dashboards in SaaS products for customers
Data governance: Ensure consistent metric definitions across organization
Self-service BI: Empower non-technical users with pre-modeled data
Multi-tenant analytics: Separate customer data with row-level security
Complex data modeling: Advanced relationships and calculations
Looker vs Alternatives
vs Tableau: Looker better governance, code-based; Tableau better visualization, drag-and-drop
vs Power BI: Looker better for embedding, governance; Power BI 10x cheaper
vs Mode: Looker better for business users; Mode better for SQL analysts
Unique Strengths
LookML modeling: Code-based metric definitions with version control
Metric governance: Single source of truth enforced across organization
Embedded analytics: Best-in-class for white-label customer dashboards
Google Cloud native: Deep BigQuery integration and performance
Bottom line: For data teams who code. Expensive but solves metric inconsistency. If "revenue" means 10 different things in your company, Looker fixes that.