You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 book_publishing_company
【Schema】
# Table: titleauthor
[
(au_id:TEXT, Primary Key, Examples: [172-32-1176, 213-46-8915, 238-95-7766]),
(title_id:TEXT, Primary Key, Examples: [PS3333, BU1032, BU2075]),
(au_ord:INTEGER, Examples: [1, 2, 3]),
(royaltyper:INTEGER, Examples: [100, 40, 30])
]
# Table: roysched
[
(title_id:TEXT, Examples: [BU1032, PC1035, BU2075]),
(lorange:INTEGER, Examples: [0, 5001, 2001]),
(hirange:INTEGER, Examples: [5000, 50000, 2000]),
(royalty:INTEGER, Examples: [10, 12, 14])
]
# Table: titles
[
(title_id:TEXT, Primary Key, Examples: [BU1032, BU1111, BU2075]),
(title:TEXT),
(type:TEXT, Examples: [business, mod_cook, UNDECIDED]),
(pub_id:TEXT, Examples: [1389, 0736, 0877]),
(price:REAL, Examples: [19.99, 11.95, 2.99]),
(advance:REAL, Examples: [5000.0, 10125.0, 0.0]),
(royalty:INTEGER, Examples: [10, 24, 12]),
(ytd_sales:INTEGER, Examples: [4095, 3876, 18722]),
(notes:TEXT),
(pubdate:DATETIME, Examples: [1991-06-12 00:00:00])
]
# Table: employee
[
(emp_id:TEXT, Primary Key, Examples: [A-C71970F, A-R89858F, AMD15433F]),
(fname:TEXT, Examples: [Aria, Annette, Ann]),
(minit:TEXT, Examples: [M, R, F]),
(lname:TEXT, Examples: [Cruz, Roulet, Devon]),
(job_id:INTEGER, Examples: [10, 6, 3]),
(job_lvl:INTEGER, Examples: [87, 152, 200]),
(pub_id:TEXT, Examples: [1389, 9999, 9952]),
(hire_date:DATETIME, Examples: [1991-10-26 00:00:00])
]
# Table: authors
[
(au_id:TEXT, Primary Key, Examples: [172-32-1176, 213-46-8915, 238-95-7766]),
(au_lname:TEXT, Examples: [White, Green, Carson]),
(au_fname:TEXT, Examples: [Johnson, Marjorie, Cheryl]),
(phone:TEXT, Examples: [408 496-7223, 415 986-7020, 415 548-7723]),
(address:TEXT, Examples: [10932 Bigge Rd., 309 63rd St. #411, 589 Darwin Ln.]),
(city:TEXT, Examples: [Menlo Park, Oakland, Berkeley]),
(state:TEXT, Examples: [CA, KS, TN]),
(zip:TEXT, Examples: [94025, 94618, 94705]),
(contract:TEXT, Examples: [0])
]
# Table: sales
[
(stor_id:TEXT, Primary Key, Examples: [6380, 7066, 7067]),
(ord_num:TEXT, Primary Key, Examples: [6871, 722a, A2976]),
(ord_date:DATETIME, Examples: [1994-09-14 00:00:00]),
(qty:INTEGER, Examples: [5, 3, 50]),
(payterms:TEXT, Examples: [Net 60, Net 30, ON invoice]),
(title_id:TEXT, Primary Key, Examples: [BU1032, PS2091, PC8888])
]
# Table: jobs
[
(job_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(job_desc:TEXT, Examples: [New Hire - Job not specified]),
(min_lvl:INTEGER, Examples: [10, 200, 175]),
(max_lvl:INTEGER, Examples: [10, 250, 225])
]
# Table: publishers
[
(pub_id:TEXT, Primary Key, Examples: [0736, 0877, 1389]),
(pub_name:TEXT, Examples: [New Moon Books, Binnet & Hardley, Algodata Infosystems]),
(city:TEXT, Examples: [Boston, Washington, Berkeley]),
(state:TEXT, Examples: [MA, DC, CA]),
(country:TEXT, Examples: [USA, Germany, France])
]
# Table: discounts
[
(discounttype:TEXT, Examples: [Initial Customer, Volume Discount, Customer Discount]),
(stor_id:TEXT, Examples: [8042]),
(lowqty:INTEGER, Examples: [100]),
(highqty:INTEGER, Examples: [1000]),
(discount:REAL, Examples: [10.5, 6.7, 5.0])
]
# Table: stores
[
(stor_id:TEXT, Primary Key, Examples: [6380, 7066, 7067]),
(stor_name:TEXT, Examples: [Eric the Read Books, Barnum's, News & Brews]),
(stor_address:TEXT, Examples: [788 Catamaugus Ave., 567 Pasadena Ave., 577 First St.]),
(city:TEXT, Examples: [Seattle, Tustin, Los Gatos]),
(state:TEXT, Examples: [WA, CA, OR]),
(zip:TEXT, Examples: [98056, 92789, 96745])
]
# Table: pub_info
[
(pub_id:TEXT, Primary Key, Examples: [0877, 1389, 1622]),
(logo:BLOB),
(pr_info:TEXT)
]
【Foreign keys】
titleauthor.au_id=authors.au_id
titleauthor.title_id=titles.title_id
roysched.title_id=titles.title_id
titles.pub_id=publishers.pub_id
employee.job_id=jobs.job_id
employee.pub_id=publishers.pub_id
sales.stor_id=stores.stor_id
sales.title_id=titles.title_id
discounts.stor_id=stores.stor_id
pub_info.pub_id=publishers.pub_id

    【Question】
    Name the store with ID 7066 and calculate the percentage of the the quantity ordered that were on 'Net 30' payment terms. store with ID 7066 refers to stor_ID = '7066'; 'Net 60' payment terms refers to payterm = 'Net 60'; qty is abbreviation for quantity; percentage = DIVIDE(payterms = 'Net 60', sum(qty))*100

    【Evidence】
    store with ID 7066 refers to stor_ID = '7066'; 'Net 60' payment terms refers to payterm = 'Net 60'; qty is abbreviation for quantity; percentage = DIVIDE(payterms = 'Net 60', sum(qty))*100

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T2.stor_name , CAST(SUM(CASE WHEN payterms = 'Net 30' THEN qty ELSE 0 END) AS REAL) * 100 / SUM(qty) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id WHERE T1.stor_id = '7066' GROUP BY T2.stor_name