Which of the following would MOST effectively ensure an organization developing AI systems has comprehensive data classification and inventory management?

Question

Options

• ACreating a centralized team to oversee the classification of data used in AI projects
• BConducting quarterly audits of AI data sets for anomalies and missing metadata
• CEstablishing a manual process to categorize data based on business needs and regulatory
• DImplementing an automated data cataloging tool that integrates with all organizational data

• A
  28% (19)
• B
  13% (9)
• C
  7% (5)
• D
  51% (34)

Explanation

Comprehensive data classification and inventory management requires coverage that scales with the organization's data volume, velocity, and variety. An automated data cataloging tool that integrates with all organizational data sources (D) provides real-time, consistent, and scalable discovery and classification across the entire data estate - eliminating gaps that manual processes create. A centralized team (A) improves governance but cannot manually keep pace with modern data volumes. Quarterly audits (B) are periodic, reactive, and will miss new data between cycles. Manual categorization (C) is error-prone, inconsistent, and not scalable. Only automation with full integration (D) can achieve truly comprehensive coverage.

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