stablecoins_evm.activity_enriched table classifies each stablecoin transfer into an activity category (for example DEX, CEX, bridge, lending, issuer).
Why these enriched tables matter
Stablecoin analysis comes down to two fundamental questions:- Where are stablecoins right now? (balances)
- How did they get there? (activity)
What this dataset is designed to do
- Explain how stablecoin balances move through the ecosystem.
- Attribute transfer activity with transparent, reproducible logic.
- Provide a defensible foundation for flow analysis.
Table schema
Value possibilities
Thecategory and activity columns are intentionally standardized so downstream models, dashboards, and monitoring can rely on deterministic value vocabularies.
This mapping enables consistent flow segmentation, KPI rollups, and alerting logic without custom per-dashboard label handling.
As protocol coverage expands, new values may be added in backward-compatible fashion.
Methodology
Classification is done at the transfer level, not the transaction level.- Start from curated stablecoin transfer rows in
stablecoins_evm.transfers. - Build candidate matches for each transfer against activity-specific datasets (for example DEX, bridge, CEX, flashloan, lending, and issuer signals) using transfer-level keys such as
tx_hash, token identity, and amount context. - Resolve conflicts with a deterministic precedence order, so each transfer gets exactly one winning category.
- Write unmatched transfers as
unidentifiedto preserve full coverage instead of dropping rows.
Important interpretation details
- One transaction can map to multiple categories if it contains multiple stablecoin transfers.
project_address,project_name, andproject_versionare populated only when a protocol/entity match exists.- Priority rules improve consistency, but edge cases still exist when protocols emit similar transfer patterns in the same transaction.
Sample query
Notes
- One transfer maps to one output row (highest-priority match wins).
- For performance, filter by
blockchainandblock_month.