Period-over-Period Change with LAG
Harbr's finance team tracks whether credit consumption is trending up or down month on month across each warehouse. Rather than joining the table to itself, you'll use LAG() to pull the previous month's credits alongside the current month's value in a single row, then compute the difference. Your task is to build that query against logistics.warehouse_usage and identify which warehouse had the largest single month-over-month increase.
This exercise is part of the course
Data Pipeline Automation in Snowflake
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