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Domain 6Objective 5

6.5 Describe Data Transformation and Mapping Within AI Agents AI-TECHNICAL-PRACTITIONER Practice Questions (Page 5)

Part of the Agentic AI domain, which accounts for 20% of the AI-TECHNICAL-PRACTITIONER exam. Cisco does not publish an official question count, but from its 60-minute exam (~25–40 total, ~5–8 in this domain), expect 1–2 from this objective — we provide 25 practice questions to prepare you well beyond it. (estimate)

25questions here
5free pages
6concepts
20%of the exam

Questions 21–25

  1. 21foundation · easy

    What is the role of data mapping in an AI agent's processing pipeline?

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  2. 22foundation · easy

    Where in an AI agent workflow does data transformation typically occur?

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  3. 23application · medium

    A customer-service AI agent receives order details from a legacy CRM. The 'order_total' field is stored as a string with a currency symbol (e.g., '$1,234.56'), while the agent's downstream pricing model requires a numeric float. Which transformation technique should the agent's preprocessing pipeline apply to this field?

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  4. 24expert · hard

    A customer-support AI agent uses a retrieval-augmented generation (RAG) workflow. User queries are embedded and compared against a vector database of past tickets. The past tickets contain a 'priority' field with values 'High', 'MEDIUM', and 'low'. The agent's response generator needs to reference priority in a consistent format. When should the priority standardization occur?

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  5. 25foundation · easy

    Which transformation technique converts categorical text labels, such as 'red', 'green', and 'blue', into a numerical format for an AI agent?

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