How do I find the correlation between two metrics with iDBQuery?

Correlation measures how closely two metrics move together, a useful clue when you are hunting for what drives an outcome. iDBQuery computes it from your data and shows the relationship visually so you can interpret it honestly.

• You'd ask iDBQuery: 'Over the last year, is weekly marketing spend correlated with new signups? Show the correlation coefficient and a scatter plot.'
• It aligns both series by period, computes the correlation, and returns a scatter or dual-axis chart with the coefficient.
• Each point is cited to its source rows, so you can verify the spend and signup figures behind the relationship.

iDBQuery is careful to keep this honest: it shows the SQL and the actual points, so you can see whether a correlation is driven by a few outliers or is genuine, and it never implies correlation equals causation. Follow-ups keep the thread: 'Does the relationship hold if we lag signups by two weeks?' or 'Check the same against a third metric.' Because the two metrics often live in different systems, marketing spend in an ad platform, signups in a product database, the one live model joins them into one answer with no pipeline. Let the Analyst agent scan several candidate drivers and report which correlates most strongly with your target metric, citing the rows. This complements root-cause and A/B analysis.