Imagine this scenario. You are in a monthly business review, and the finance department presents a slide showing that the monthly recurring revenue is $1.2 million. A few minutes later, the head of sales presents a dashboard showing that same revenue metric at $1.3 million. Both teams are adamant that their numbers are correct. A lengthy debate follows, and the data team is tasked with finding the "real" number. This situation is all too common, and it erodes the most valuable asset a data team has: trust. The problem is sometimes the source data, but more often, the problem is inconsistent business logic.