Event Studio
Democratize data by enabling teams to produce and manage datasets with full visibility into ownership, meaning, and structure. Enforce event tracking standards to ensure data quality at source while streamlining new downstream use cases.
Define and document your tracking plans in granular detail with ownership information and semantic descriptions, enabling teams to create datasets with visibility into which teams own each dataset.
Reduce time from data collection to actionable insights and real-time activation. Transform days of manual SQL work into minutes with autogenerated data models created directly in Console. Leverage Snowtype code generation to rapidly implement tracking with quick detection and correction of failed events.
Foster internal collaboration by allowing teams to subscribe to, reuse, and receive alerts about tracking plans of interest, accelerating the creation of new use cases.
Each tracking plan in Snowplow Event Studio decides whether events that break their event specification are rejected or delivered with a flag. By default, the pipeline delivers them with a validation entity that names each error, so you can query violations in your warehouse. Change the plan's data quality rules to send them to failed events instead, and they stay out of your events table. Events that fail schema validation always go to failed events.
Yes. Snowplow CLI keeps your Event Studio data structures and tracking plans as YAML or JSON files in your own repository, so every change goes through pull request review before it's published. Your CI/CD pipeline can validate each change and publish approved versions to your development and production environments. Teams that prefer a visual editor can keep working in the UI, and the Console API supports custom tooling.
Yes. Snowplow Assistant, built into Snowplow Console, creates data structures, event specifications, and tracking plans from a plain-language description, checks public schemas and what you already track so you can reuse them, and generates tracking code. To work from your own AI tool, such as Claude or Cursor, connect the Snowplow MCP server, or use the CLI MCP server to create and validate tracking plan files. The assistant and the MCP server act only within your existing permissions.
Yes. Snowplow Event Studio generates a view or an incremental dbt model from a tracking plan, flattening the events and entities you choose into one column per property for analysis, BI tools, or reverse ETL. You can also generate a semantic model for it in the open Apache Ossie format. AI agents and BI tools read it to write correct SQL, and its descriptions come from your tracking plan, not from AI.
Yes. In Snowplow Event Studio, each tracking plan works as a data contract between the teams that produce data and the teams that use it. Data structures define and validate every event and entity, each plan has an explicit owner, and subscribers are notified when the plan changes. Event specification validation then checks incoming events against the plan's rules, such as allowed values and required entities.
Snowplow Assistant works only with Snowplow configuration and metadata, such as schemas, tracking plans, pipeline settings, and failed event error details, and has no access to personal data. It uses your existing permissions and asks for confirmation before it changes anything. Your messages and the configuration it retrieves are processed by a third-party LLM provider. An administrator accepts those terms before it's enabled and can turn it off for the whole organization.
Snowplow versions every data structure, so a change normally creates a new version rather than overwriting the old one. Non-breaking changes, such as adding an optional field, increase the minor version. Breaking changes, such as adding a required field or changing a field's type, increase the major version. The builder picks the right version for you, and subscribers to a tracking plan are notified when it changes.
Send test events to a development environment in Snowplow Console, which runs Snowplow Micro and validates them against your schemas and your draft event specifications, then check the results in the Micro dashboard. Micro also runs locally with Docker and works for automated tests in your CI/CD pipeline. For web tracking, the Snowplow Inspector browser extension lets you check each event as you browse your site.
Create a live trial environment, send your first events, then work with it from your own coding tool through the MCP server or ask Snowplow Assistant in the console. No expert required, no credit card, no sales call.
