How does iDBQuery build a trend line or time series from my data?

Trends over time are the backbone of reporting, and building one correctly means getting the date field, the grain, and the boundaries right.

• Bucket by period. iDBQuery groups rows into the time buckets you ask for — "monthly revenue this year", "weekly active users", "daily orders" — using the appropriate date column.
• Right grain and window. It resolves relative ranges ("last 12 months") to concrete dates and respects your fiscal calendar if defined, so periods line up with how you actually report.
• Handles the awkward bits. Missing periods, partial current periods, and period-over-period comparisons (MoM, YoY) are handled in the generated SQL rather than left for you to reconcile.

The result renders as a line or bar chart you can refine — change the grain, add a comparison period, overlay a second metric — and pin to a dashboard or export. Because iDBQuery shows the SQL and cites each point back to its source rows, a trend isn't just a suggestive shape; you can trace any month's value to the records behind it. That's what makes its time series safe to put in front of a board or use to spot a genuine change rather than a charting artefact.