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Analytics is Chaos

Without Taxonomy

Curate taxonomy with schema-first tracking infra that is type-safe & self-documenting. 📈

Try Voltage-Schema

Note: this code editor simulates the functionality of voltage-schema, but does not actually run the npm package.

Edit the YAML schema, then experiment with the type-safe tracker.

📝 YAML Schema
⚡ TypeScript Tracker
🖥️ CLI Outputnpm voltage generate

CLI output will appear here when you modify the YAML schema

The Journey Towards Data Maturity 🧙‍♂️

Organizations follow a natural progression in their analytics journey:

1

No Tracking

Teams fly blind with no data.

2

Basic Tracking

Teams add analytics as needs arise.

3

Chaotic Tracking

The data is there, but so is the chaos & knowledge silos.

4

Organized Taxonomy

Data quality champions have laid the ground rules of taxonomy. Chaos is down, but knowledge silos are still up.

5

Self-Documenting Analytics

As the app evolves, a never stale autodoc of analytics taxonomy gets generated from schemas.

6

Augmented Analytics

Analytics data becomes part of an interconnected platform to power workflows & in-app personalization.

7

AI Ready Analytics

Evolutionary schema context is generated for use by AI agents, so that over time they get increasingly better at analyzing & understanding your data.

Voltage is designed to help your organization scale all the way from stage 2 - 7 while following industry standard best practices. ⚡