Describe the Data Analytics Lifecycle Purpose and Sequence of Phases DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   What is the main objective of the Discovery phase in the data analytics lifecycle?

   • ATo deploy the final model into a production environment.
   • BTo understand the business problem and identify the data and resources needed for the project.
   • CTo build and train predictive models using the prepared data.
   • DTo clean and transform raw data into a format suitable for analysis.
   Reveal Solution Discussion Select an answer first
2. 17expert · hard

   A retail company is in the communicating results phase of a project to analyze customer purchasing behavior. The team has prepared a detailed technical report, but the business executives who will make decisions do not have a technical background. What should the team do to ensure the results are actionable?

   • ACreate a high-level summary with visualizations and key takeaways for the executives.
   • BDelay the presentation until executives complete technical training.
   • CSkip the presentation and send the technical report via email.
   • DPresent the technical report as-is and let executives ask questions.
   Reveal Solution Discussion Select an answer first
4. 18application · medium

   A manufacturing company wants to reduce equipment downtime using sensor data. The analytics team is considering skipping the discovery phase to save time and start analyzing data immediately. Why is this approach likely to fail?

   • AThe discovery phase is required to deploy the model to production.
   • BWithout discovery, the team may not understand the business problem or have clear success criteria.
   • CSkipping discovery prevents the team from building any model at all.
   • DThe discovery phase is where the data is cleaned and prepared for analysis.
   Reveal Solution Discussion Select an answer first
5. 19expert · hard

   A logistics company is using the data analytics lifecycle for a route optimization project. After deploying the model in the operationalization phase, the team discovers that the model's performance degrades over time because traffic patterns change seasonally. What is the most appropriate action according to the lifecycle?

   • AIgnore the degradation because the model was validated during model building.
   • BRemove the model from production and abandon the project.
   • CReturn to the discovery phase to redefine the business problem.
   • DContinue monitoring the model and periodically retrain it with new data.
   Reveal Solution Discussion Select an answer first
6. 20application · medium

   A retail company has collected years of transaction data. The analytics team has been asked to identify factors that drive customer churn. The team has already met with business stakeholders to define the problem and has inventoried the available data sources. According to the data analytics lifecycle, what should the team do next?

   • ACommunicate preliminary findings to stakeholders to confirm the problem statement.
   • BDeploy a churn-scoring model into production to begin generating insights immediately.
   • CProceed to the data preparation phase, cleaning and transforming the identified data sources.
   • DBegin building a predictive model using the most promising variables.
   Reveal Solution Discussion Select an answer first