Modern Data Quality Requires a Rethink
It is 2023 and why are we still talking about data quality? Twilight Zone? Deja Vu? Every vendor promises a new fangled approach that they claim is better and will cure all ills of the past. But, we know better.
But, do we?
What if the space of data quality is going through a rethink, driven by the tremendous demands for accurate data from AI and ML use cases? After all, what good do sophisticated models, like ChatGPT, do if they are trained on faulty data? That faulty data may not even be visible to the naked eye. The data itself may be correct, but arrived in the system a tad bit too late or is biased.