How do I do week-over-week and month-over-month analysis with iDBQuery?
Ask iDBQuery 'How did revenue change week over week and month over month, with the percentage difference?' It compares each period to the one before across your data, returns the growth rates as a chart, and cites every figure back to the source rows behind it.
Week-over-week (WoW), month-over-month (MoM), and quarter-over-quarter (QoQ) comparisons show how a metric is changing between consecutive periods, the fastest read on momentum. iDBQuery computes these growth rates without you writing lag-and-difference SQL.
- You'd ask iDBQuery: 'Show revenue by week for the last quarter with the WoW percentage change, and by month with the MoM change.'
- It aligns each period with the prior one, computes the absolute and percentage change, and returns a chart plus a table.
- Each figure is cited to its source rows, so 'MoM growth = +8%' can be traced to both months' underlying records.
Unlike year-over-year, which controls for seasonality, WoW and MoM catch short-term shifts, and you can run both in one thread to separate momentum from seasonal effects: 'Now show the same months year over year.' iDBQuery keeps the context. Because the metric may draw on several sources, the one live model computes the comparison across all of them with no pipeline. When a period swings sharply, pivot straight to diagnosis: 'Break the MoM drop down by region.' Save it as a live report for the weekly standup, and let the Analyst agent flag which periods and segments moved most, citing the rows. This is a building block for variance and trend analysis.
Updated 2026-06-22