case when tx_receiver = 'token.sweat' then 'Sweat Token' when tx_receiver like '%token.near%' then 'Near token' else 'Other Token' end as token_type,

count(

distinct(tx_hash)

) as no_of_txns,

count(

distinct(tx_signer)

) as no_of_users,

round(no_of_txns / no_of_users, 2) as avg_txns_per_day

from

near.core.fact_transactions

where

tx_status = 'Success'

and block_timestamp >= dateadd(

month,

-3,

getdate()

)

group by

token_type