Skip to content

Onchain Analytics System #40

Description

@thalescb

Context

GoodDollar's onchain data was scattered across subgraphs, Google Apps Script pipelines, block explorers, and loose Dune dashboards -- no centralized, reliable view of protocol activity existed. The idea emerged in early 2026 to build a proper analytics system.

Journey so far:

  1. Hypersync discovery -- Hadar pointed to Hypersync as an indexing solution; studied it, built the first ingestion pipeline
  2. BigQuery as the warehouse -- researched storage options; chose BigQuery for cost, public dataset capability, and SQL familiarity
  3. MVP: XDC invites pipeline -- first end-to-end pipeline (Hypersync to BigQuery to Looker Studio dashboard), validating the architecture
  4. dbt migration -- 10 models across staging/semantic/marts, 57 tests, full documentation and governance framework
  5. Production deployment -- all models live in BigQuery, dbt docs site operational

Goal

A production-grade onchain analytics system: centralized, automated, documented, and expandable -- so any team member can query protocol activity without asking the data team.

Scope

  • Hypersync ingestion pipeline (MVP)
  • BigQuery warehouse setup
  • XDC invites dashboard (architecture validation)
  • dbt migration -- 10 models, staging to semantic to marts
  • Documentation and governance framework (analytics contract, business glossary, freshness macros)
  • Pipeline hardening -- error handling, retries, alerting
  • Scheduled execution -- cron/Cloud Scheduler
  • Expansion: additional contract events (phased -- each entity gets its own sub-issue as scoped)
  • Centralized metric dictionary (dbt-native, evolves with expansion)

Current Status

Production-deployed with 10 models and 57 passing tests. Data freshness stale since Jun 7 -- pipeline hardening is the critical path to fix this. Hadar greenlit the approach after a demo (Jul 6).

Value

Moves GoodDollar from "ask Thales to pull the data" to "query it yourself." Foundation for every dashboard, metric, and reporting cadence downstream.

References

  • Project folder: projects/onchain-analytics/
  • dbt docs: generated locally via dbt docs generate
  • dbt models: projects/onchain-analytics/gd_dbt/

Metadata

Metadata

Assignees

Labels

epicInitiative-level tracking issuein-progressActively being worked oninfrastructurePipeline, systems, and platform work

Type

No type

Projects

Status
Backlog

Milestone

No milestone

Relationships

None yet

Development

No branches or pull requests

Issue actions