That the organization has documented lawful rights: Following data governance requirements, what must the team
Data governance requires documented lawful rights and a valid basis to use the data for the intended training purpose before training starts.
The question
A data science team wants to train a model on a large dataset of customer interactions that was originally collected for a different, unrelated purpose. Following data governance requirements, what must the team establish before using this data for training?
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- That the dataset is large enough to satisfy the model's statistical power needs, since data volume drives training reliability the most.Plausible but wrong: sufficient quantity is one data-quality dimension, but it cannot cure the absence of a lawful basis to reuse the data.
- That the storage location for the dataset is encrypted at rest so the confidentiality of the customer interactions is protected during training.Plausible but wrong: encryption is a sound security control but does not establish the lawful right to repurpose the data.
- That the model architecture selected can process the data format efficiently so training runs complete within the project's time budget.Plausible but wrong: architecture-data fit is an engineering concern, not the lawful-basis question data governance requires be resolved first.
- That the organization has documented lawful rights and a valid basis to use the data for the new training purpose, before any training begins. ✓Correct: data governance requires assessing and documenting lawful rights and a valid basis to use data, especially for a new, unrelated purpose.
The trap
Assuming that data quantity or security controls can substitute for a lawful basis to reuse data. How to remember it
Data governance requires documented lawful rights and a valid basis to use the data for the intended training purpose before training starts.
How many of these would you get right?
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