Data Readiness Checklist for Industrial AI Pilots
Concise checklist to evaluate whether process, sensor, and business data meet the practical needs of an AI pilot project.
Sections:
1) Signal inventory & sampling rates.
2) Data quality checks: gaps, timestamps, duplicates.
3) Labeling readiness and ground truth availability.
4) Ownership, access, and retention.
5) Privacy, safety, and human-in-the-loop considerations.
6) Success criteria & minimal viable dataset definition.
Includes a simple scoring model to compare pilot candidates.
Discussion
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