Describe the Business Drivers for Big Data Analytics and Data Science DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 4)

Questions 16–20

1. 16expert · hard

   A logistics company has a data lake with years of shipment data, but the data is stored in inconsistent formats across different business units. The data science team wants to build a predictive model for delivery delays. The IT team estimates it will take six months to standardize the data. The operations team needs the model in two months to negotiate new client contracts. What is the best course of action?

   • ABuild a model using a subset of data from the most consistent business unit, then expand as data is standardized
   • BAsk the operations team to delay contract negotiations until the data is ready
   • CHire a third-party vendor to build the model immediately, ignoring internal data
   • DWait six months for the fully standardized data because any model built on inconsistent data is invalid
   Reveal Solution Discussion Select an answer first
2. 17application · medium

   A city transportation department wants to optimize bus schedules. They have GPS data from buses, passenger boarding counts, and traffic patterns. The data science team is asked to build a model that predicts route demand by time of day. What is the main way this model supports the department's decision-making?

   • AIt provides evidence-based forecasts that allow schedule adjustments to match actual demand
   • BIt automatically purchases new buses based on predicted demand
   • CIt guarantees that buses will always be on time regardless of traffic
   • DIt replaces the need for traffic engineers to analyze any data
   Reveal Solution Discussion Select an answer first
4. 18application · medium

   A logistics firm captures GPS tracks from 10,000 vehicles every 30 seconds, generating terabytes of data daily. The data is stored in a data lake but is rarely queried because the volume makes traditional analysis slow. The firm hires a data scientist to improve route optimization. Which statement best describes the relationship between the Big Data and the data scientist's work?

   • ABig Data provides the raw material and scale that the data scientist uses to build better predictive models
   • BBig Data replaces the need for a data scientist because the data is already clean and structured
   • CBig Data and data science are unrelated because data science only works with small, curated datasets
   • DThe data scientist's main job is to reduce the volume of data so it fits in a spreadsheet
   Reveal Solution Discussion Select an answer first
5. 19expert · hard

   A retail bank wants to improve customer retention. The analytics team proposes two models: Model 1 predicts churn using only transaction data, which is already available. Model 2 predicts churn using transaction data plus social media sentiment, which requires purchasing a third-party data feed. Model 2 is expected to be 5% more accurate. The bank has a strict budget and a compliance team that is wary of external data. What should the bank do?

   • AImmediately implement Model 2 because higher accuracy always justifies additional cost
   • BImplement Model 2 but hide the external data from the compliance team
   • CStart with Model 1 to establish a baseline, then evaluate whether the added accuracy of Model 2 justifies the cost and compliance risk
   • DReject both models because churn prediction is not a valid business driver
   Reveal Solution Discussion Select an answer first
6. 20foundation · medium

   A retail company analyzes customer purchase histories to identify cross-selling opportunities. Which business driver does this primarily support?

   • AData storage cost reduction
   • BRegulatory compliance
   • CRevenue growth
   • DIT infrastructure consolidation
   Reveal Solution Discussion Select an answer first