Where to go next | GraphJSON Docs

Once you are comfortable with collect → visualize → export, choose the next step based on the problem you are solving.

Ask more complex questions#

Use the SQL notebook for joins, window functions, cohort analysis, deduplication, or calculations that do not map cleanly to visualizer controls.

Then work through:

Put analytics in your product#

Start with Embed graphs to understand static and dynamic embeds.

For internal reporting and read-only sharing, use Manage and share dashboards.

For user-specific views, follow Personalized dashboards. It explains how to keep the API key on your server while changing a filter for each authenticated user.

Before a customer-facing launch, use Production embedded analytics for tenant isolation, caching, states, accessibility, and testing.

For build-time generation, use Static deployments.

Harden ingestion#

Review:

Migrate or connect existing systems#

GraphJSON can receive data from Segment, Stripe, and Vercel. For another provider, build a narrow custom-source webhook adapter. Use integrations when the source already emits the events you need; use the logging API when you need a product-specific event contract.

To bring historical data with you, use the migration runbooks for Amplitude, Mixpanel, PostHog, and Google Analytics 4.

Start from a complete architecture#

Adapt one of the production references:

A production-readiness checklist#

Before treating a metric as a source of truth:

document who owns its event instrumentation
use stable event and field names
keep monetary values numeric and include a currency
attach durable user or account identifiers
choose an explicit retention policy
handle ingestion failures without breaking your application
reconcile a sample period against the source system
document the chart’s filters, time zone, and aggregation

The goal is not merely to make a chart. It is to make a number another person can understand, reproduce, and trust.