Solutions:

1.
SELECT 
  SKU_Code, 
  Category, 
  Weight,
  RANK() OVER (PARTITION BY Category ORDER BY Weight DESC) AS Weight_Rank
FROM Products;

2.
SELECT 
  ROW_NUMBER() OVER (ORDER BY Date) AS Row_Num,
  Sale_ID, 
  Date, 
  Gross_Amount
FROM Sales_Transactions;

3.
WITH CustomerSpending AS (
  SELECT 
    c.Customer_ID, 
    c.Customer_Name,
    SUM(s.Gross_Amount) AS Total_Spent
  FROM Customers c
  JOIN Sales_Transactions s ON c.Customer_ID = s.Customer_ID
  GROUP BY c.Customer_ID, c.Customer_Name
)
SELECT 
  Customer_ID, 
  Customer_Name, 
  Total_Spent,
  DENSE_RANK() OVER (ORDER BY Total_Spent DESC) AS Spend_Rank
FROM CustomerSpending;

4.
WITH RankedProducts AS (
  SELECT 
    Category,
    SKU_Code,
    Weight,
    RANK() OVER (PARTITION BY Category ORDER BY Weight DESC) AS Weight_Rank
  FROM Products
)
SELECT * FROM RankedProducts
WHERE Weight_Rank <= 3;

5.
SELECT 
  Operation_ID,
  Operation_Type,
  ROW_NUMBER() OVER (PARTITION BY Operation_Type ORDER BY Operation_ID) AS Seq_Num
FROM Warehouse_Ops;

6.
SELECT 
  Sale_ID,
  EXTRACT(MONTH FROM Date) AS Month,
  Gross_Amount,
  RANK() OVER (PARTITION BY EXTRACT(MONTH FROM Date) ORDER BY Gross_Amount DESC) AS Monthly_Rank
FROM Sales_Transactions;

7.
SELECT 
  s.SKU_Code,
  s.Date,
  s.Gross_Amount AS Daily_Sales,
  SUM(s.Gross_Amount) OVER (PARTITION BY s.SKU_Code ORDER BY s.Date) AS Running_Total
FROM Sales_Transactions s
JOIN Products p ON s.SKU_Code = p.SKU_Code;

8.
WITH InventoryValues AS (
  SELECT 
    p.Category,
    i.SKU_Code,
    (i.Stock_Qty * pr.TP_Price) AS Inventory_Value,
    PERCENT_RANK() OVER (PARTITION BY p.Category ORDER BY (i.Stock_Qty * pr.TP_Price) DESC) AS Value_Percentile
  FROM Inventory i
  JOIN Pricing pr ON i.SKU_Code = pr.SKU_Code
  JOIN Products p ON i.SKU_Code = p.SKU_Code
)
SELECT * FROM InventoryValues
WHERE Value_Percentile <= 0.1;

9.
WITH CustomerPurchases AS (
  SELECT 
    c.Customer_ID,
    c.Customer_Name,
    MAX(s.Gross_Amount) AS Max_Purchase
  FROM Customers c
  JOIN Sales_Transactions s ON c.Customer_ID = s.Customer_ID
  GROUP BY c.Customer_ID, c.Customer_Name
)
SELECT 
  Customer_ID,
  Customer_Name,
  Max_Purchase,
  RANK() OVER (ORDER BY Max_Purchase DESC) AS Purchase_Rank
FROM CustomerPurchases;

10.
WITH MonthlySales AS (
  SELECT 
    EXTRACT(MONTH FROM Date) AS Month,
    SUM(Gross_Amount) AS Monthly_Sales,
    LAG(SUM(Gross_Amount)) OVER (ORDER BY EXTRACT(MONTH FROM Date)) AS Previous_Month_Sales
  FROM Sales_Transactions
  GROUP BY EXTRACT(MONTH FROM Date)
)
SELECT 
  Month,
  Monthly_Sales,
  Previous_Month_Sales,
  (Previous_Month_Sales - Monthly_Sales) AS Sales_Drop
FROM MonthlySales
ORDER BY Sales_Drop DESC
LIMIT 1;

11.
WITH ProductSales AS (
  SELECT 
    p.SKU_Code,
    p.Design_No,
    COALESCE(SUM(s.Quantity), 0) AS Total_Sold
  FROM Products p
  LEFT JOIN Sales_Transactions s ON p.SKU_Code = s.SKU_Code
  GROUP BY p.SKU_Code, p.Design_No
)
SELECT 
  SKU_Code,
  Design_No,
  Total_Sold,
  PERCENT_RANK() OVER (ORDER BY Total_Sold) AS Sales_Percentile
FROM ProductSales;

12.
WITH CustomerDates AS (
  SELECT DISTINCT
    Customer_ID,
    Date
  FROM Sales_Transactions
),
DateGroups AS (
  SELECT 
    Customer_ID,
    Date,
    DATE_ADD(Date, -ROW_NUMBER() OVER (PARTITION BY Customer_ID ORDER BY Date)) AS Date_Group
  FROM CustomerDates
)
SELECT 
  Customer_ID,
  COUNT(*) AS Consecutive_Days
FROM DateGroups
GROUP BY Customer_ID, Date_Group
HAVING COUNT(*) > 1;

13.
WITH CategoryPrices AS (
  SELECT 
    p.Category,
    AVG(s.Gross_Amount/s.Quantity) AS Avg_Sale_Price
  FROM Products p
  JOIN Sales_Transactions s ON p.SKU_Code = s.SKU_Code
  GROUP BY p.Category
)
SELECT 
  Category,
  Avg_Sale_Price,
  RANK() OVER (ORDER BY Avg_Sale_Price DESC) AS Category_Rank
FROM CategoryPrices;

14.
WITH MonthlyRanks AS (
  SELECT 
    c.Customer_ID,
    c.Customer_Name,
    EXTRACT(MONTH FROM s.Date) AS Month,
    SUM(s.Gross_Amount) AS Monthly_Spend,
    PERCENT_RANK() OVER (PARTITION BY EXTRACT(MONTH FROM s.Date) 
      ORDER BY SUM(s.Gross_Amount) DESC) AS Spend_Percentile
  FROM Customers c
  JOIN Sales_Transactions s ON c.Customer_ID = s.Customer_ID
  GROUP BY c.Customer_ID, c.Customer_Name, EXTRACT(MONTH FROM s.Date)
)
SELECT 
  Customer_ID,
  Customer_Name,
  COUNT(*) AS Top_Months
FROM MonthlyRanks
WHERE Spend_Percentile <= 0.25
GROUP BY Customer_ID, Customer_Name
HAVING COUNT(*) = (SELECT COUNT(DISTINCT EXTRACT(MONTH FROM Date)) FROM Sales_Transactions);

15.
WITH DailySales AS (
  SELECT 
    Date,
    SUM(Gross_Amount) AS Daily_Sales
  FROM Sales_Transactions
  GROUP BY Date
)
SELECT 
  Date,
  Daily_Sales,
  AVG(Daily_Sales) OVER (ORDER BY Date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS Moving_Avg_7day
FROM DailySales;