m 30C Haze n 4. Question 4 An online store wants to analyze various aspects of...

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m 30°C Haze n 4. Question 4 An online store wants to analyze various aspects of using coupons, including the distribution of discounts and savings. The company is developing a report that displays the total number of orders that used coupon codes and the average savings per order for orders using coupon codes. The result should have the following columns: total_orders | total amount | total_unique_coupons_uses | total savings | avg_savings_per_order. . . ● total_orders- the total number of orders that used coupon codes total amount - the total amount of orders that used coupon codes total_unique_coupons_uses- the total number of unique coupon codes that have been . redeemed total_savings - the total amount of money saved by using coupon codes, rounded to two decimal places avg_savings_per_order- the average savings per order for orders using coupon codes, rounded to two decimal places Note: Only orders that used coupon codes should be included in the report. Schema Schema . Only orders that used coupon codes should be included in the report. name id coupon_code discount percent name id coupon_id type INT VARCHAR(255) type INT INT INT to coupons total amount DECIMAL(5,2) coupons constraint PRIMARY KEY UNIQUE orders constraint Q Search PRIMARY KEY description Coupon Code ID Unique code of the coupon Percentage discount offered description Order ID Reference to the coupon Order total 30°C Haze 30°C Haze n ► Sample Data Tables ► Expected Output id coupon_code discount_percent 1 COUPON123 2 3 5 8 11 12 14 18 id coupon_id total amount 1 3 14 1 18 3 4 20 2 15 16 6 7 9 SAVE20 DISCOUNT50 1 1 1 1 1 1 1 2 2 2 2 2 2 3 coupons 3 3 null null null orders 34.10 80.06 94.57 84.04 50.30 9.03 10.49 JUDU 97.15 10.49 97.15 9.03 30 78.60 15.59 76.77 30 89.38 25 0.33 23.00 51.00 45.82 D ↳ Q Search Q Search 3-4/5 ALL O 3 4 5 6 7 8 2h 45m left ALL O 1 2 3 4 5 6 7 1 S 3 4 20 2 15 16 6 7 9 10 13 17 19 4 20 15 16 a. 6 7 9 10 13 17 2 19 2 ▸ Expected Output 2 2 13 3 3 3 null null null 15.59 Text selection has been disabled in this region null null null null 2 3 3 null null null null null null null ▾ Expected Output 97.15 9.03 78.60 15.59 76.77 89.38 0.33 23.00 51.00 45.82 81.98 47.72 2.09 68.56 78.60 89.38 0.33 23.00 51.00 45.82 81.98 47.72 2.09 68.56 total_orders total amount total_unique_coupons_uses total_savings avg_savinį 720.41 4 3 207.80 1! m 30°C Haze n 4. Question 4 An online store wants to analyze various aspects of using coupons, including the distribution of discounts and savings. The company is developing a report that displays the total number of orders that used coupon codes and the average savings per order for orders using coupon codes. The result should have the following columns: total_orders | total amount | total_unique_coupons_uses | total savings | avg_savings_per_order. . . ● total_orders- the total number of orders that used coupon codes total amount - the total amount of orders that used coupon codes total_unique_coupons_uses- the total number of unique coupon codes that have been . redeemed total_savings - the total amount of money saved by using coupon codes, rounded to two decimal places avg_savings_per_order- the average savings per order for orders using coupon codes, rounded to two decimal places Note: Only orders that used coupon codes should be included in the report. Schema Schema . Only orders that used coupon codes should be included in the report. name id coupon_code discount percent name id coupon_id type INT VARCHAR(255) type INT INT INT to coupons total amount DECIMAL(5,2) coupons constraint PRIMARY KEY UNIQUE orders constraint Q Search PRIMARY KEY description Coupon Code ID Unique code of the coupon Percentage discount offered description Order ID Reference to the coupon Order total 30°C Haze 30°C Haze n ► Sample Data Tables ► Expected Output id coupon_code discount_percent 1 COUPON123 2 3 5 8 11 12 14 18 id coupon_id total amount 1 3 14 1 18 3 4 20 2 15 16 6 7 9 SAVE20 DISCOUNT50 1 1 1 1 1 1 1 2 2 2 2 2 2 3 coupons 3 3 null null null orders 34.10 80.06 94.57 84.04 50.30 9.03 10.49 JUDU 97.15 10.49 97.15 9.03 30 78.60 15.59 76.77 30 89.38 25 0.33 23.00 51.00 45.82 D ↳ Q Search Q Search 3-4/5 ALL O 3 4 5 6 7 8 2h 45m left ALL O 1 2 3 4 5 6 7 1 S 3 4 20 2 15 16 6 7 9 10 13 17 19 4 20 15 16 a. 6 7 9 10 13 17 2 19 2 ▸ Expected Output 2 2 13 3 3 3 null null null 15.59 Text selection has been disabled in this region null null null null 2 3 3 null null null null null null null ▾ Expected Output 97.15 9.03 78.60 15.59 76.77 89.38 0.33 23.00 51.00 45.82 81.98 47.72 2.09 68.56 78.60 89.38 0.33 23.00 51.00 45.82 81.98 47.72 2.09 68.56 total_orders total amount total_unique_coupons_uses total_savings avg_savinį 720.41 4 3 207.80 1!

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To create a report that displays the total number of orders that used coupon codes and the average savings per order for orders using coupon codes you ... View the full answer