Updated 2022-11-08
    with alamedaftx as (
    select *
    from solana.core.dim_labels
    where label like '%alameda%' or label like 'ftx%' or address_name ilike '%alameda%' or address_name ilike 'ftx%')
    select block_timestamp::date as date,
    initcap (label) as Destination,
    count (distinct tx_id) as TX_Count,
    sum (amount) as Outflow_Volume,
    sum (Outflow_Volume) over (partition by destination order by date) as Cumulative_Volume
    from solana.core.fact_transfers t1 join solana.core.dim_labels t2 on t1.tx_to = t2.address
    where tx_from in (select distinct address from alamedaftx)
    and tx_to not in (select distinct address from alamedaftx)
    and mint in ('EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v','Es9vMFrzaCERmJfrF4H2FYD4KCoNkY11McCe8BenwNYB','Ea5SjE2Y6yvCeW5dYTn7PYMuW5ikXkvbGdcmSnXeaLjS','7kbnvuGBxxj8AG9qp8Scn56muWGaRaFqxg1FsRp3PaFT','EnuaX3ogrr2CaoAPjtaKHAoBNWok32BMcRozuf32s2QF','USDH1SM1ojwWUga67PGrgFWUHibbjqMvuMaDkRJTgkX','9iLH8T7zoWhY7sBmj1WK9ENbWdS1nL8n9wAxaeRitTa6','EYpdBuyAHSbdaAyD1sKkxyLWbAP8uUW9h6uvdhK74ij1')
    and block_timestamp > CURRENT_DATE - 30
    group by 1,2
    order by 1
    Run a query to Download Data