financial Database Schema

SQL Query:

SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.gender = 'M' AND T2.A2 = 'Hl.m. Praha'

Evidence:

District data appears in the A2; Male means that gender = 'M'

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.account_id FROM account AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.A3 = 'Prague' ORDER BY T1.date ASC LIMIT 1

Evidence:

A3 stands for region names

SQL Query:

SELECT T3.client_id FROM `order` AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id INNER JOIN disp AS T4 ON T4.account_id = T2.account_id  INNER JOIN client AS T3 ON T4.client_id = T3.client_id WHERE T1.order_id = 32423

SQL Query:

SELECT COUNT(T2.client_id) FROM district AS T1 INNER JOIN client AS T2 ON T1.district_id = T2.district_id WHERE T2.gender = 'F' AND STRFTIME('%Y', T2.birth_date) < '1950' AND T1.A2 = 'Sokolov'

Evidence:

Customers refer to clients; Female refers to gender = 'F'; Names of districts appear in column A2