Why BI Teams Choose Consistency Over Accuracy

Photo by Oyemike Princewill on Unsplash

“Why don’t these numbers match?”
If you’ve ever worked in a BI or analytics team, you’ve heard this question more times than you’d like to admit.

I remember a meeting where three dashboards — built by three different teams — reported three different revenue numbers. Same data source. Same time period. Different answers.
The silence that followed was louder than the numbers themselves.

Here’s the uncomfortable truth: most BI teams prefer consistency over accuracy. Not because they don’t care about precision — but because inconsistent numbers erode trust faster than incorrect ones.

The Root of the Problem

In most organizations, metrics are defined in silos. One team calculates “Customer Lifetime Value” one way, another team uses a different formula. Over time, these discrepancies multiply, leading to confusion, misalignment, and costly decision-making errors.

This is where Databricks Metric Views come in.

Enter Metric Views: One Definition to Rule Them All

Databricks recently introduced Metric Views (currently in Public Preview), a feature that allows teams to define KPIs once and use them everywhere — across…