Is gemini-3.5-flash-high good at Data & Analytics?

“The model correctly identifies correlation vs. causation and reverse causality, and provides excellent business recommendations. However, it completely misses survivorship bias (selecting on the dependent variable), which is a critical flaw in the executive's reasoning and an explicitly stated failure mode for this task. It fails to point out that the executive only looked at successful accounts and ignored unsuccessful or churned accounts.”

“While the model correctly calculates and reports both the absolute (1 percentage point) and relative (50%) reductions, its core conclusion completely fails the benchmark. It explicitly treats an observational association as proven causation ('halves', 'prevent one adverse event', 'mitigating risk') and fabricates statistical significance, violating the core rules of honest data communication.”