snowflake
for data engineers
Steady1
signal score
1
live items
↓ Cooling
7-day est. ~0
Why this scored 1
every term, weightedEngagement per hour, normalized against the fastest item on its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities are talking about the same entity
Decays to zero over 14 days
Subtracted once something is big and old — we rank what's next, not what's peaked
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On a topic's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement. Full methodology
Outlook
low confidence · estimate, not a guarantee7-day
~0
range 0–0
14-day
~0
range 0–0
30-day
~0
range 0–0
Signal history
7-day window (free)— — projected trajectory (estimate, not a guarantee)
The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
- 18
I wanted Snowflake to do more than store data. So I built a pipeline where it judges World Cup conviction, then writes its verdict back to Solana. The architecture ended up being my favorite part of the project.
Data pipeline architecture — for data engineers
devtodataSteady11d ago - 28
For the love of the game: a World Cup companion with on-chain betting and Snowflake-ready analytics
World cup companion built — for data engineers
devtodataSteady15d ago - 37
Snowflake Cortex, Explained Like an AI That Lives Next to Your Data
Snowflake explained with AI — for data engineers
devtodataSteady6d ago