CREATE TABLE Services (Service_ID NUMBER, Service_name VARCHAR2)
CREATE TABLE Customers_Policies (Customer_ID NUMBER, Policy_ID NUMBER, Date_Opened DATE, Date_Closed DATE)
CREATE TABLE Claims (Claim_ID NUMBER, FNOL_ID NUMBER, Effective_Date DATE)
CREATE TABLE Customers (Customer_ID NUMBER, Customer_name VARCHAR2)
CREATE TABLE Settlements (Settlement_ID NUMBER, Claim_ID NUMBER, Effective_Date DATE, Settlement_Amount FLOAT)
CREATE TABLE First_Notification_of_Loss (FNOL_ID NUMBER, Customer_ID NUMBER, Policy_ID NUMBER, Service_ID NUMBER)
CREATE TABLE Available_Policies (Policy_ID NUMBER, policy_type_code CHAR, Customer_Phone VARCHAR2)

Retrieve the close dates of all the policies associated with the customer whose name contains 'Diana', bin the close dates into the day of week interval and count them for a bar chart, and display from high to low by the total number.
SELECT Date_Closed, COUNT(Date_Closed) FROM Customers AS t1 JOIN Customers_Policies AS t2 ON t1.Customer_ID = t2.Customer_ID WHERE t1.Customer_name LIKE "%Diana%" ORDER BY COUNT(Date_Closed) DESC
SELECT "Date_Closed", COUNT("Date_Closed") FROM "Customers" "t1" JOIN "Customers_Policies" "t2" ON "t1"."Customer_ID" = "t2"."Customer_ID" WHERE "t1"."Customer_name" LIKE "%Diana%" ORDER BY COUNT("Date_Closed") DESC