The cleanest way to resolve conflicting KPIs across dashboards is to shift the conversation away from the dashboards themselves and toward the underlying data lineage and metric definitions. When two teams pull numbers from different layers one from raw tables and one from a curated reporting model they’re not just visualizing data differently; they’re answering slightly different questions without realizing it. The first step is to trace both pipelines back to their origins: understand which tables they use, what transformations are applied, and where filters, joins, or timestamp logic diverge. This almost always reveals the root of the mismatch. From there, compare the definitions instead of the SQL. Subtle differences like how “active users” are counted, whether test accounts are excluded, or whether refunds are reversed lead to major output gaps. Once you understand both perspectives, evaluate which version best reflects the real-world business process. Sometimes the curated layer is more precise; sometimes the raw layer is more aligned with actual operations.