Describe the Business Drivers for Big Data Analytics and Data Science DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 5)

Questions 21–25

1. 21expert · hard

   A multinational retailer wants to use Big Data to personalize marketing across regions. The EU region has strict data residency laws, while the US region does not. The analytics team proposes a single global model trained on all customer data. The legal team objects. What is the most appropriate strategic approach?

   • AAbandon personalization entirely because of the legal complexity
   • BTrain separate regional models so each region's data stays within its legal boundaries
   • CMove all data to the US to simplify the model
   • DProceed with the global model because the legal team is being overly cautious
   Reveal Solution Discussion Select an answer first
2. 22expert · hard

   A utility company has smart meter data from millions of customers, but the data is noisy and contains many gaps. The analytics team wants to build a model to predict peak demand. The IT department suggests cleaning the data first, which will take three months. The operations team needs the model in one month to plan for the upcoming summer. What is the best way to reconcile these constraints?

   • AWait the three months for perfect data because any model built on noisy data is worthless
   • BBuild a preliminary model with the available data now, and refine it as the data is cleaned
   • CAbandon the project because the data quality issues are insurmountable
   • DAsk the operations team to delay summer planning until the data is clean
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4. 23expert · hard

   A healthcare provider wants to reduce emergency room wait times. The analytics team proposes a model that predicts patient inflow based on historical data, weather, and local events. The model would allow the hospital to adjust staffing levels. However, the nursing union requires that staffing changes be announced 48 hours in advance. The model currently provides predictions only 24 hours ahead. What is the most appropriate action?

   • ACancel the project because the model cannot meet the 48-hour requirement
   • BUse the 24-hour model as a guide but combine it with a longer-term forecasting method to meet the 48-hour staffing rule
   • CIgnore the union rule because the model's predictions are more important
   • DAsk the union to change the rule to 24 hours
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5. 24foundation · medium

   A bank uses a predictive model to identify customers likely to churn. How does this demonstrate the role of data science in business?

   • AIt guarantees that no customer will leave the bank
   • BIt provides insights that enable proactive customer retention strategies
   • CIt replaces the need for customer service representatives
   • DIt automates the bank's loan approval process
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6. 25foundation · medium

   How can Big Data analytics influence an organization's strategic planning?

   • ABy focusing only on short-term operational metrics
   • BBy guaranteeing that all strategic decisions will be successful
   • CBy replacing the need for a formal business strategy
   • DBy providing insights into market trends and customer behavior that inform strategic decisions
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