SQL MoM Growth Using LAG: Formulas and Three Common Traps
Learn how to write month-over-month growth queries in SQL using LAG(), understand the exact formula, and avoid three hidden calculation traps.
Stock photo for illustration only, not from the actual event
- MoM growth formula is this month minus last month, divided by last month.
- The LAG() function fetches the previous row's value onto the current row.
- Watch out for three traps: integer division, empty first month, and missing months.
Calculating month-over-month (MoM) growth is a core data analysis task, but writing SQL queries for it requires careful attention to detail. According to data analyst Michael Nocito on Dev.to, mastering the LAG() function and recognizing hidden calculation pitfalls is essential to ensure your growth metrics are reliable and error-free.
The foundational formula for growth is straightforward: take this month's revenue, subtract last month's revenue, and divide the difference by last month's base. For instance, if January revenue was 250 and February was 300, the difference of 50 divided by 250 yields 0.2, or a 20% growth rate. Dividing by the prior month turns raw changes into scalable percentages that remain comparable regardless of business size.
In practice, utilizing the LAG() window function in SQLite (available since version 3.25) allows analysts to pull the previous row's revenue into a new column on the current row. However, raw order data must first be aggregated to a monthly grain using GROUP BY, transforming individual transaction rows into distinct monthly summaries before window functions can be effectively applied.
"Revenue grew 20% month over month, from 250 in January to 300 in February."
Stock photo for illustration only, not from the actual event
AI Insight & Context: Window functions like LAG() are powerful tools for time series analysis in SQL because they allow row-to-row comparisons without collapsing the underlying dataset. However, their primary limitation is positional rather than calendar-based awareness. If a month has zero transactions and is completely missing from the database, LAG() will bridge the gap and compare non-adjacent calendar months, leading to silent calculation errors unless explicitly handled.
The three major traps when computing MoM growth in SQL include integer division truncating decimals, the natural absence of a prior month for the initial data point, and missing months in the timeline. Analysts should always verify distinct month counts against the calendar before trusting any growth query output.
Source: Dev.to
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