Analyze Requirements for AI-powered Business Solutions AB-100 Practice Questions (Page 2)

Questions 6–10

1. 6application · medium

   A manufacturing company wants to deploy an agent that automates the creation of purchase orders from inventory levels. The inventory data is stored in multiple spreadsheets with different column names and formats. The agent will need to access this data programmatically. What should the team do to make the data usable by the agent?

   • AConvert the spreadsheets to PDF files for easier sharing.
   • BKeep the spreadsheets as-is and train the agent to interpret each format.
   • CConsolidate the spreadsheets into a single structured database with a consistent schema.
   • DCreate a new spreadsheet that combines all data without changing the original files.
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2. 7application · medium

   A utility company wants to use an AI agent to analyze energy consumption patterns and predict peak demand. The data is stored in a legacy system with inconsistent field names and units. What should the architect do to make the data usable by the agent?

   • AProvide the agent with the raw data and let it infer the schema.
   • BConvert all data to a single unit, such as kilowatt-hours, but keep field names as-is.
   • CUse only a subset of the data that is already consistent.
   • DTransform the data into a standardized schema with consistent units and field names.
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4. 8foundation · easy

   How can an AI agent support business decision-making?

   • ABy making all decisions autonomously without human oversight
   • BBy eliminating the need for historical data in decision-making
   • CBy providing data-driven recommendations and forecasts
   • DBy ensuring that decisions are always correct and unbiased
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5. 9foundation · easy

   Why is it important to assess the relevance of data before building an AI solution?

   • ARelevant data is always free of errors
   • BRelevant data is always easier to collect than irrelevant data
   • CRelevant data is always stored in a specific format
   • DIrrelevant data can confuse the AI model and reduce its performance
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6. 10application · medium

   A retail company wants to use an AI agent to generate daily sales summaries for regional managers. The agent will pull data from a data warehouse that contains sales transactions, product returns, and inventory levels. The data warehouse is updated hourly, but the agent's summary is generated at 8:00 AM each day. What should the architect configure to ensure the summaries reflect the most recent data?

   • ASchedule the agent to run at 8:00 AM and have it query the data warehouse directly at that time.
   • BUse the agent's built-in memory to store the previous day's summary and append new transactions.
   • CCreate a nightly snapshot of the data warehouse at midnight and ground the agent on that snapshot.
   • DHave the agent use its training data to infer sales trends instead of querying the warehouse.
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