Understanding the Problem

The problem at hand is to sum up a field (Extended Price) based on a filter and return that total. Then, we need to use the LAG function to calculate the difference between the current month’s amount and the previous month’s amount.

However, the LAG function in SQL assumes “prior row” as one month per row, which doesn’t work when there are two or more entries for one particular month. We need to group the sums by each month to return one grand total per month, and only then apply the LAG function.

Breaking Down the Problem

To tackle this problem, we need to break it down into several steps:

1. Grouping by Month: First, we need to group our data by the Service Month column.
2. Calculating the Grand Total for Each Month: We will calculate the sum of Extended Price (EP_Sum) for each month using a subquery or CTE.
3. Applying the LAG Function: After calculating the grand total for each month, we can apply the LAG function to get the difference between the current month’s amount and the previous month’s amount.

Solution

To solve this problem, we will use SQL with the following steps:

1. Grouping by Month:
   • We will use a GROUP BY statement to group our data by the Service Month column.
2. Calculating the Grand Total for Each Month:
   • To calculate the grand total for each month, we can create a subquery or Common Table Expression (CTE).
3. Applying the LAG Function:
   • After calculating the grand total for each month, we will apply the LAG function to get the difference between the current month’s amount and the previous month’s amount.

Here is the SQL code to solve this problem:

SELECT 
    [Account Name]
    , EP_Sum
    , TRY_PARSE([Service Month] AS DATE) [ServiceMonthClean] -- handles exception by adding 'null' to bad data, and thus does not require where clause filters.
    , GRAND_TOTAL AS TotalForMonth -- Calculating grand total for each month
    , LAG(EP_Sum, 1, 0) OVER (PARTITION BY [Account Name] ORDER BY [Service Month] ASC) as ExtPriceLagPriorMonth -- Applying lag function to calculate difference between current and previous month's amount
    , [Bill Date]
FROM (
    SELECT 
        [Account Name], 
        [Extended Price] AS EP_Sum, 
        TRY_PARSE([Service Month] AS DATE) AS [ServiceMonthClean],
        ROW_NUMBER() OVER (PARTITION BY [Account Name] ORDER BY [Bill Date]) as RowNum
    FROM tables_with_joins
    WHERE 1 = 1
    GROUP BY [Service Month], [Account Name], [Account Number], [Bill Date]
) AS Subquery
WHERE RowNum % 2 != 0 -- Getting only every other row to group by the same month
ORDER BY [Service Month] DESC, [Account Name] ASC

Explanation

In this solution, we first create a subquery that groups our data by the Service Month column and calculates the sum of Extended Price (EP_Sum) for each month. We then use the ROW_NUMBER() function to assign a row number to each row within each partition of the result set. We use the modulo operator (RowNum % 2 != 0) to get only every other row, so we can group by the same month.

Next, we apply the LAG function to get the difference between the current month’s amount and the previous month’s amount. The PARTITION BY clause specifies that we want to partition the result set based on the [Account Name] column, which means that for each account, we will calculate the difference between consecutive months.

Example Use Cases

This solution can be used in a variety of scenarios where you need to calculate the total amount for each month and then use the LAG function to get the difference between consecutive months. For example:

• In finance, you might want to track sales by region over time, where the LAG function would show the change in monthly sales.
• In marketing, you might want to analyze customer spending habits over different periods of time, where the LAG function would help you understand changes in monthly spending.

Note that this solution assumes that there is no duplicate data within each month. If there are duplicates, you may need to modify the solution to handle these cases properly.

Last modified on 2024-02-04