financial Database Schema

SQL Query:

SELECT COUNT(T1.account_id) FROM account AS T1 INNER JOIN disp AS T2 ON T1.account_id = T2.account_id WHERE T2.type = 'OWNER' AND T1.frequency = 'POPLATEK PO OBRATU'

Evidence:

Frequency = 'POPLATEK PO OBRATU' stands for issuance after transaction

SQL Query:

SELECT COUNT(account_id) FROM trans WHERE STRFTIME('%Y', date) > '1995' AND operation = 'VYBER KARTOU'

Evidence:

Operation = 'VYBER KARTOU' means credit card withdrawals

SQL Query:

SELECT COUNT(T1.account_id) FROM account AS T1 INNER JOIN loan AS T2 ON T1.account_id = T2.account_id INNER JOIN district AS T3 ON T1.district_id = T3.district_id WHERE T3.A3 = 'Prague'

Evidence:

A3 contains the data of region

SQL Query:

SELECT CAST(SUM(T1.gender = 'M') AS REAL) * 100 / COUNT(T1.client_id) FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.A3 = 'south Bohemia' GROUP BY T2.A4 ORDER BY T2.A4 DESC LIMIT 1

Evidence:

Percentage of the male clients = DIVIDE(COUNT(male clients), COUNT(clients)) * 100; Male refers to gender = 'M', A3 is the region name. A4 contains the information about inhabitants.

SQL Query:

SELECT T1.client_id FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN account AS T5 ON T2.account_id = T5.account_id INNER JOIN loan AS T3 ON T5.account_id = T3.account_id INNER JOIN card AS T4 ON T2.disp_id = T4.disp_id WHERE T1.gender = 'F'

Evidence:

Female refers to gender = 'F'