Solutions:

1. 
   SELECT AVG(Weight) AS Avg_Weight
   FROM Products;
   

2. 
   WITH AvgWeight AS (
     SELECT AVG(Weight) AS avg_val FROM Products
   )
   SELECT SKU_Code, Design_No, Weight
   FROM Products, AvgWeight
   WHERE Weight > avg_val;
   

3. 
   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
   HAVING SUM(s.Gross_Amount) > (SELECT AVG(Gross_Amount) FROM Sales_Transactions);
   

4. 
   WITH MonthlySales AS (
     SELECT EXTRACT(MONTH FROM Date) AS Month, SUM(Gross_Amount) AS Total_Sales
     FROM Sales_Transactions
     GROUP BY EXTRACT(MONTH FROM Date)
   )
   SELECT * FROM MonthlySales;
   

5. 
   SELECT i.SKU_Code, (i.Stock_Qty * p.TP_Price) AS Inventory_Value
   FROM Inventory i
   JOIN Pricing p ON i.SKU_Code = p.SKU_Code
   WHERE (i.Stock_Qty * p.TP_Price) > (
     SELECT AVG(Stock_Qty * TP_Price)
     FROM Inventory JOIN Pricing ON Inventory.SKU_Code = Pricing.SKU_Code
   );
   

6. 
   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 *, RANK() OVER (ORDER BY Total_Spent DESC) AS Rank
   FROM CustomerSpending;
   

7. 
   SELECT p.SKU_Code, p.Design_No
   FROM Products p
   WHERE NOT EXISTS (
     SELECT DISTINCT EXTRACT(MONTH FROM Date)
     FROM Sales_Transactions
     WHERE EXTRACT(MONTH FROM Date) NOT IN (
       SELECT DISTINCT EXTRACT(MONTH FROM Date)
       FROM Sales_Transactions s
       WHERE s.SKU_Code = p.SKU_Code
     )
   );
   

8. 
   WITH SalesWithTotal AS (
     SELECT 
       Sale_ID, 
       Date, 
       Gross_Amount,
       SUM(Gross_Amount) OVER (ORDER BY Date) AS Running_Total
     FROM Sales_Transactions
   )
   SELECT * FROM SalesWithTotal;
   

9. 
   SELECT SKU_Code, Design_No
   FROM Products p
   WHERE NOT EXISTS (
     SELECT 1 FROM Sales_Transactions s
     WHERE s.SKU_Code = p.SKU_Code
   );
   

10. 
    WITH RECURSIVE CategoryHierarchy AS (
      SELECT Category, 1 AS Level
      FROM Products
      WHERE Category NOT LIKE '%-%'
      
      UNION ALL
      
      SELECT p.Category, ch.Level + 1
      FROM Products p
      JOIN CategoryHierarchy ch ON p.Category LIKE CONCAT(ch.Category, '-%')
    )
    SELECT * FROM CategoryHierarchy;
    

11. 
    SELECT c.Customer_ID, c.Customer_Name
    FROM Customers c
    WHERE NOT EXISTS (
      SELECT p.Category
      FROM Products p
      WHERE NOT EXISTS (
        SELECT 1
        FROM Sales_Transactions s
        WHERE s.Customer_ID = c.Customer_ID
        AND s.SKU_Code IN (
          SELECT SKU_Code FROM Products 
          WHERE Category = p.Category
        )
      )
    );
    

12. 
    WITH ProductSales AS (
      SELECT p.SKU_Code, p.Design_No, SUM(s.Gross_Amount) AS Total_Sales
      FROM Products p
      LEFT JOIN Sales_Transactions s ON p.SKU_Code = s.SKU_Code
      GROUP BY p.SKU_Code, p.Design_No
    ),
    TotalSales AS (
      SELECT SUM(Gross_Amount) AS total FROM Sales_Transactions
    )
    SELECT 
      ps.SKU_Code, 
      ps.Design_No,
      ROUND((ps.Total_Sales / ts.total) * 100, 2) AS Pct_Total_Sales
    FROM ProductSales ps, TotalSales ts;
    

13. 
    WITH PriceConsistency AS (
      SELECT 
        SKU_Code,
        CASE 
          WHEN Amazon_MRP = Flipkart_MRP AND Flipkart_MRP = Myntra_MRP THEN 'Yes'
          ELSE 'No'
        END AS Is_Consistent
      FROM Pricing
    )
    SELECT * FROM PriceConsistency;
    

14. 
    WITH CategoryAverages AS (
      SELECT 
        p.Category, 
        AVG(s.Gross_Amount) AS Avg_Spending
      FROM Sales_Transactions s
      JOIN Products p ON s.SKU_Code = p.SKU_Code
      GROUP BY p.Category
    ),
    CustomerCategorySpending AS (
      SELECT 
        c.Customer_ID, 
        c.Customer_Name,
        p.Category,
        SUM(s.Gross_Amount) AS Total_Spent
      FROM Customers c
      JOIN Sales_Transactions s ON c.Customer_ID = s.Customer_ID
      JOIN Products p ON s.SKU_Code = p.SKU_Code
      GROUP BY c.Customer_ID, c.Customer_Name, p.Category
    )
    SELECT ccs.*
    FROM CustomerCategorySpending ccs
    JOIN CategoryAverages ca ON ccs.Category = ca.Category
    WHERE ccs.Total_Spent > ca.Avg_Spending;
    

15. 
    WITH ProductPairs AS (
      SELECT 
        a.SKU_Code AS Product1, 
        b.SKU_Code AS Product2,
        COUNT(*) AS Frequency
      FROM Sales_Transactions a
      JOIN Sales_Transactions b ON a.Sale_ID = b.Sale_ID AND a.SKU_Code < b.SKU_Code
      GROUP BY a.SKU_Code, b.SKU_Code
      HAVING COUNT(*) > 1
    )
    SELECT 
      CONCAT(Product1, ' + ', Product2) AS Product_Pair,
      Frequency
    FROM ProductPairs
    ORDER BY Frequency DESC;