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SQL/Bike Store.sql
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119
SQL/Bike Store.sql
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create database BikeStore
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-- Adding Foreign Keys
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---- Products
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ALTER TABLE products
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ADD CONSTRAINT Brand_to_Prod
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FOREIGN KEY (brand_id) REFERENCES brands(brand_id);
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ALTER TABLE products
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ADD CONSTRAINT Cat_to_Prod
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FOREIGN KEY (category_id) REFERENCES categories(category_id);
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---- Staffs
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ALTER TABLE staffs
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ALTER COLUMN store_id TINYINT
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ALTER TABLE staffs
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ADD CONSTRAINT Store_to_Staff
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FOREIGN KEY (store_id) REFERENCES stores(store_id);
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---- Stocks
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ALTER TABLE stocks
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ADD CONSTRAINT Store_to_Stock
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FOREIGN KEY (store_id) REFERENCES stores(store_id);
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ALTER TABLE stocks
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ADD CONSTRAINT Prod_to_Stock
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FOREIGN KEY (product_id) REFERENCES products(product_id);
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---- Orders
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ALTER TABLE orders
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ADD CONSTRAINT PK_Orders
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PRIMARY KEY (order_id);
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ALTER TABLE orders
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ADD CONSTRAINT Cust_to_Orders
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FOREIGN KEY (customer_id) REFERENCES customers(customer_id);
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ALTER TABLE orders
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ADD CONSTRAINT Store_to_Orders
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FOREIGN KEY (store_id) REFERENCES stores(store_id);
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ALTER TABLE orders
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ADD CONSTRAINT Staff_to_Orders
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FOREIGN KEY (staff_id) REFERENCES staffs(staff_id);
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--- Order_Items
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ALTER TABLE order_items
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ADD CONSTRAINT orderItems_to_orders
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FOREIGN KEY (order_id) REFERENCES orders(order_id);
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-- BEGINNER LEVELS
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--- Retrieve a list of full names and ID's of customers in the database.
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SELECT DISTINCT
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[Customer ID] = customer_id,
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[Full Name] = CONCAT(first_name, ' ',last_name)
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FROM
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BikeStore.dbo.customers
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--- Find the total number of orders placed by each customer, sort it from largest to smallest.
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SELECT
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[Customer ID] = C.customer_id,
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[Full Name] = CONCAT(C.first_name, ' ',C.last_name),
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[Order Count] = COUNT(O.order_id)
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FROM
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BikeStore.dbo.customers C join BikeStore.dbo.orders O on C.customer_id = O.customer_id
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GROUP BY
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C.customer_id, C.first_name, C.last_name
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ORDER BY
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[Order Count] desc
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--- List all the products in a specific category.
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SELECT
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[Category] = category_name,
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[Product Name] = product_name
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FROM products P join categories C on P.category_id = C.category_id
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--- Calculate the total sales (without discount) for a specific store.
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SELECT
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[Store Name] = store_name,
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[Total Sales] = CAST(SUM(O.list_price*quantity) as INT)
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FROM
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stores S join orders D on S.store_id = D.store_id join order_items O on D.order_id = O.order_id
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GROUP BY
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store_name
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ORDER BY
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[Store Name] desc
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--- Get the names of staff members working at Baldwin Bikes.
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SELECT
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[Full Name] = CONCAT(S.first_name, ' ',S.last_name)
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FROM
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staffs S join stores T on S.store_id = T.store_id
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WHERE T.store_name like 'Baldwin Bikes'
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--- Find the brands of products that are out of stock.
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SELECT DISTINCT
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[Brand] = B.brand_name,
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[Stock] = S.quantity
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FROM brands B join products P on B.brand_id = P.brand_id join stocks S on S.product_id = P.product_id
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WHERE S.quantity = 0
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--- Identify the store names, couunt of them buying from that store, placed by Onita Johns.
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SELECT
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[Full Name] = CONCAT(C.first_name, ' ',C.last_name),
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[Store Name] = S.store_name,
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[Count of Orders] = COUNT(order_id)
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FROM customers C join orders O on C.customer_id = O.customer_id join stores S on O.store_id = S.store_id
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WHERE C.first_name like 'Onita' AND C.last_name like 'Johns'
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GROUP BY
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C.first_name, C.last_name, S.store_name
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--- List all products that are only ordered <=5 times.
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SELECT
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[Product Name] = P.product_name,
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[Order Count] = COUNT(O.order_id)
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FROM order_items O join products P on P.product_id = O.product_id
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GROUP BY P.product_name
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HAVING COUNT(O.order_id) < 5 or COUNT(O.order_id) = 5
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146
SQL/main.sql
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146
SQL/main.sql
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-- Calculate the total revenue generated by each store for year 2018.
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SELECT
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[Store Name] = S.store_name,
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[Gross Revenue] = FORMAT(SUM(OI.list_price*OI.quantity), 'N0'),
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[Net Revenue] = FORMAT(SUM((OI.list_price*OI.quantity)-((OI.list_price*OI.quantity)*OI.discount)), 'N0')
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FROM
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order_items OI join orders O on O.order_id = OI.order_id join stores S on O.store_id = S.store_id
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WHERE
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YEAR(O.order_date) = 2018
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GROUP BY
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S.store_name
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-- Find the top 5 selling products across all stores based on the quantity sold.
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WITH RankedProducts AS (
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SELECT
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[Product Name] = P.product_name,
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[qty_Sold] = SUM(OI.quantity),
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[RANK] = DENSE_RANK() OVER (ORDER BY SUM(OI.quantity) DESC)
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FROM
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order_items OI
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JOIN products P ON OI.product_id = P.product_id
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GROUP BY
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P.product_name
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)
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SELECT DISTINCT
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[Product Name],
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[qty_Sold],
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[RANK]
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FROM
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RankedProducts
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WHERE
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[RANK] <= 5;
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-- Retrieve Jamaal Albert and Melia Brady's order history, including the order date, product details, and total amount spent.
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SELECT
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[Customer Name] = CONCAT(CU.first_name , ' ' , CU.last_name),
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[Order Date] = O.order_date,
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[Product details] = P.product_name,
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[Category] = C.category_name,
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[Amount spent] = FORMAT(SUM((OI.list_price*OI.quantity)-((OI.list_price*OI.quantity)*OI.discount)),'N0')
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FROM
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orders O
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join order_items OI on O.order_id = OI.order_id
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join products P on OI.product_id = P.product_id
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join categories C on P.category_id = C.category_id
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join customers CU on CU.customer_id = O.customer_id
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WHERE (CU.first_name = 'Jamaal' and CU.last_name = 'Albert') OR (CU.first_name = 'Melia' and CU.last_name = 'Brady')
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GROUP BY
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CONCAT(CU.first_name, ' ' , CU.last_name), O.order_date, P.product_name, C.category_name
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ORDER BY
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[Customer Name] asc
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-- List the products that are running low on stock (quantity less than 10) in each store.
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SELECT
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[Store Name] = S.store_name,
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[Product Name] = P.product_name,
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[Stocks] = SUM(ST.quantity)
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FROM
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stores S join stocks ST on S.store_id = ST.store_id join products P on ST.product_id = P.product_id
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GROUP BY store_name, product_name
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HAVING SUM(ST.quantity) < 10
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ORDER BY [Stocks] desc
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-- List the products that are running low on stock (quantity less than 10) in each store.
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SELECT
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[Store Name],
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[Product Name],
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[Sum Qty]
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FROM (
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SELECT
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[Store Name] = S.store_name,
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[Product Name] = P.product_name,
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[Sum Qty] = SUM(ST.quantity)
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FROM
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stores S join stocks ST on S.store_id = ST.store_id join products P on ST.product_id = P.product_id
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GROUP BY
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store_name, product_name
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) as SUBQQ
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WHERE [Sum Qty] < 10
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-- Identify the top 5 staff members who have processed the highest total value of orders.
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SELECT TOP 5
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[Staff Name] = CONCAT(ST.first_name, ' ' , ST.last_name),
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[Orders Processed] = COUNT(O.order_id)
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FROM staffs ST join orders O on ST.staff_id = O.staff_id
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GROUP BY ST.first_name, ST.last_name
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ORDER BY [Orders Processed] desc
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-- category wise sales percentage XX
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SELECT
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[Category Name] = C.category_name,
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[Total Sales] = FORMAT(SUM((OI.list_price*OI.quantity)-((OI.list_price*OI.quantity)*OI.discount)),'N0'),
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[Percentage] = FORMAT((SUM((OI.list_price*OI.quantity)-((OI.list_price*OI.quantity)*OI.discount)) /
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SUM(SUM((OI.list_price * OI.quantity) - ((OI.list_price * OI.quantity) * OI.discount))) OVER ()),'#.##%')
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FROM
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categories C join products P on C.category_id = P.category_id join order_items OI on OI.product_id = P.product_id
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GROUP BY C.category_name
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ORDER BY [Percentage] desc
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-- Identify staff members who are marked as inactive (1) and have not processed any orders.
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SELECT
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[Staff Name] = CONCAT(S.first_name, ' ' , S.last_name)
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FROM staffs S join orders O on O.staff_id = S.staff_id
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WHERE S.active = 1
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GROUP BY S.first_name, S.last_name
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HAVING count(O.order_id) = 0
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-- Customer Loyalty
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WITH Loyalty AS(
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SELECT
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[Customer Name] = CONCAT(C.first_name, ' ' , C.last_name),
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[Stores] = S.store_name,
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[Store_Orders] = COUNT(DISTINCT S.store_name),
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[Count_Orders] = COUNT(O.order_id),
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[Avg_Spending] = AVG((OI.list_price*OI.quantity)-((OI.list_price*OI.quantity)*OI.discount))
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FROM
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customers C
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join orders O on C.customer_id = O.customer_id
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join order_items OI on O.order_id = OI.order_id
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join stores S on S.store_id = O.store_id
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GROUP BY
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C.first_name, C.last_name, S.store_name, O.order_id
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)
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SELECT
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[Customer Name],
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[Stores],
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[Count_Orders],
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[Avg_Spending]
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FROM
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Loyalty
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WHERE [Store_Orders] > 1
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-- Calculate the average discount amount applied to products in each product category.
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SELECT
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[Product Category] = C.category_name,
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[Average Discount] = FORMAT(AVG(OI.list_price*OI.discount),'N0')
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FROM
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categories C
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join products P on C.category_id = P.category_id
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join order_items OI on OI.product_id = P.product_id
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GROUP BY
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C.category_name
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