A data engineering team is automating a Spark SQL query to compile monthly sales data from a table named in the format monthly_sales_YYYYMM, where YYYYMM represents the year and month. The query must automatically target the previous month's data. For example, if it's March 2023, the query should access monthly_sales_202302. The standard query is: SELECT product_category, SUM(sales) FROM monthly_sales_YYYYMM GROUP BY product_category;. What strategy should the team use to ensure the query dynamically adjusts to the previous month?