Design consistent event tracking schemas for analytics.
Event Schema Architect
Amplitude, Mixpanel, Segment
Best for
- ▸Design normalized event taxonomies for product analytics across Amplitude, Mixpanel, and Segment
- ▸Create property standards and validation rules for consistent tracking across engineering teams
- ▸Architect JSON Schema definitions for event tracking with forward/backward compatibility
- ▸Build tracking plans that prevent duplicate events and ensure semantic consistency
What you'll get
- ▸Hierarchical event taxonomy with Object-Action naming (e.g., page_viewed, item_added_to_cart) plus required/optional property definitions
- ▸JSON Schema specifications with validation rules, enum constraints, and semantic business rules for each event type
- ▸Schema versioning strategy with migration patterns and backward compatibility guidelines for analytics platform evolution
Product domain context, user journey definitions, analytics objectives, and existing tracking implementations that need normalization.
Comprehensive event schema documentation with taxonomies, property standards, JSON Schema validation rules, and implementation guidelines.
What's inside
“You are an Event Schema Architect. You design event tracking schemas that prevent analytics debt and catch broken tracking before it reaches the warehouse. - **Hunt for silent failures and semantic duplicates** -- Most teams ship button_click and btn_clicked in the same codebase without noticing. Yo...”
Covers
Not designed for ↓
- ×Real-time event stream processing or pipeline architecture
- ×Data warehouse modeling or dimensional schema design
- ×Analytics dashboard creation or visualization design
- ×Event processing business logic or ETL transformations
SupaScore
88.55▼
Evidence Policy
Standard: no explicit evidence policy.
Research Foundation: 7 sources (3 official docs, 3 books, 1 industry frameworks)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
v5.5 final distill
Pipeline v4: rebuilt with 3 helper skills
Initial release
Works well with
Need more depth?
Specialist skills that go deeper in areas this skill touches.
Common Workflows
Analytics Implementation Pipeline
Design normalized schemas, implement tracking instrumentation, then validate data quality across analytics platforms
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