This article provides an in-depth look at the LAG function, covering its syntax, practical use cases, and how it can enhance your data analysis skills.
Understanding the LAG Function
The LAG function is an SQL window function that lets you retrieve data from a previous row in the same result set, eliminating the need for self-joins.
Basic Syntax
The basic syntax of the LAG function is:
LAG(expression [, offset [, default_value]]) OVER ( [PARTITION BY partition_expression, ... ] ORDER BY sort_expression [ASC | DESC], ... )
expression: The column or expression whose value you want to retrieve from a previous row.offset: (Optional) The number of rows to look back. Default is 1 if not specified.default_value: (Optional) The value to return if the offset goes beyond the scope of the partition.
Practical Applications of the LAG Function to find Anomalies
In this example, we have a STORE_SALE table that contains transaction data for each store for a given day.
We'll use the LAG function to compare sales from one month to the previous month. If the sales increase by 1.8 times or more, we'll flag it as an "Anomaly." Otherwise, it will be considered a normal trend.
To compare the sales values between the current and previous month, we'll apply the LAG function.
Below is the SQL syntax for detecting anomalies in sales:
Select
YEAR,
MONTH,
SALE,
COALESCE(SALE_LAST_MONTH,SALE) As SALE_LAST_MONTH,
TRANSACTION_FLAG
From (
SELECT
YEAR(D_DATE) AS YEAR,
MONTH(D_DATE) As MONTH,
SUM(SALE_PRICE) AS SALE,
LAG(SALE) OVER(PARTITION BY YEAR ORDER BY MONTH) As SALE_LAST_MONTH,
CASE WHEN SALE>= 1.8*SALE_LAST_MONTH THEN 'Potential Anomaly' ELSE 'Normal' END As TRANSACTION_FLAG
FROM
STORE_SALES
GROUP BY
YEAR,
Month
)
ORDER BY
YEAR,
MONTH;
Hope this article has helped you in understanding lag function. Happy Learning !!!!!!!!!
