Data Management Specific to AI AAIA Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   What does data lineage primarily enable an AI auditor to do?

   • ADelete data that is no longer needed
   • BTrace the flow of data from its origin through transformations to its use in model outputs
   • CEncrypt data to protect it from unauthorized access
   • DAnonymize personal data to protect privacy
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2. 2foundation · easy

   Which data preparation step involves transforming raw data into a format suitable for model training, such as normalizing numerical values?

   • AData retention
   • BData acquisition
   • CData disposal
   • DData transformation
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4. 3expert · hard

   A pharmaceutical company is developing an AI model to assist in drug discovery. The model uses proprietary research data and patient trial data. The company's legal team has mandated that patient trial data must be retained for 15 years per clinical trial regulations, but the data science team wants to delete the data as soon as the model is validated to reduce storage costs. The company also has a policy to securely dispose of data when it is no longer needed. Which disposal strategy satisfies both the regulatory retention and the secure disposal policy?

   • ADelete the patient trial data immediately after model validation and rely on the model's parameters as the only record.
   • BStore the data on a tape backup and physically destroy the tapes after 15 years.
   • CAnonymize the patient trial data and retain the anonymized version for 15 years, deleting the raw data after 1 year.
   • DRetain the patient trial data for the full 15-year period in an encrypted archive, and then perform a secure cryptographic erase (e.g., deleting the encryption keys) at the end of the retention period.
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5. 4application · medium

   A retail company is implementing a data governance framework for its AI initiatives. The company has multiple data sources, including sales transactions, customer feedback, and inventory levels. The data governance team wants to ensure that the data used for AI models is trustworthy and that the models are auditable. Which governance practice is most important to establish first?

   • ACreate a data retention policy for all AI-related data.
   • BEstablish a data catalog that documents the metadata, ownership, and quality of all data sources used for AI.
   • CImplement a data masking tool to protect sensitive data in the AI models.
   • DDeploy a data quality monitoring tool to track data quality metrics in real-time.
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6. 5foundation · easy

   What is a key architectural consideration when designing storage for AI workloads that require high-throughput data access?

   • AUsing parallel file systems or high-performance storage
   • BUsing only on-premises storage
   • CStoring all data in a single database
   • DAvoiding data compression
   Reveal Solution Discussion Select an answer first