Determine If Data Meets Solution Needs PMI-CPMAI Practice Questions (Page 2)

Questions 6–10

1. 6application · medium

   A transportation company is building a model to predict traffic accidents. The data science team has traffic volume data, weather data, and road condition data. However, they lack data on driver behavior, which the business believes is a key factor. The team is identifying data gaps. What should they do?

   • AUse traffic volume data as a proxy for driver behavior.
   • BProceed with the available data because driver behavior is difficult to measure.
   • CAsk the business to remove the driver behavior requirement from the model's scope.
   • DIdentify the driver behavior data gap and explore alternative sources, such as telematics or speed camera data.
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2. 7foundation · easy

   What is the primary purpose of comparing available data against defined requirements and specifications?

   • ATo determine the cost of acquiring additional data
   • BTo identify discrepancies between what data exists and what the solution needs
   • CTo select the best machine learning algorithm for the data
   • DTo ensure the data is stored in a secure and compliant manner
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4. 8application · medium

   A government agency is developing an AI system to process permit applications. The data science team has collected application data from the past three years. The business requirement specifies that the system must handle applications from all 50 states, but the data is heavily concentrated in five states. The team is comparing the data against the requirements. What should they do?

   • AUse the data as is and rely on the model's ability to generalize across states.
   • BCollect more data from the five states to improve the model's accuracy.
   • CProceed with the data because it covers three years of applications.
   • DDocument the geographic discrepancy and assess the impact on the model's performance for underrepresented states.
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5. 9application · medium

   A company is building a model to predict customer churn for its subscription service. The data science team has collected six months of historical data, but the business requirement specifies that the model must be trained on data that includes at least two full annual cycles to capture seasonal patterns. The team is under pressure to start modeling. What should the team do first?

   • ACompare the available data against the stated requirement and document the gap before deciding next steps.
   • BProceed with the six months of data and note the limitation in the model documentation.
   • CUse the six months of data but apply synthetic data generation to create the missing seasonal patterns.
   • DImmediately begin collecting additional data to reach two years before any modeling work.
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6. 10expert · hard

   A pharmaceutical company is developing an AI model to predict drug interactions. The data science team has access to a large dataset of clinical trials, but the data is from a limited patient population (e.g., adults only). The model will be used for pediatric patients. The team must make a go/no-go decision. What should they do?

   • AMake a no-go decision because the data is not representative of the target population.
   • BProceed with the data because it is large and from clinical trials.
   • CConduct a comprehensive data readiness assessment, weighing the representativeness gap against the potential to mitigate it, before making a go/no-go decision.
   • DProceed with the data but adjust the model's decision threshold for pediatric patients.
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