Describe the Data Scientist Role and Related Skills DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 1)

Questions 1–5

1. 1application · medium

   A retail company has a team that builds dashboards showing daily sales totals and a separate team that maintains the data pipelines feeding those dashboards. Leadership now wants to predict which products will be out of stock next week so they can adjust orders. Which role is best suited to lead this new initiative?

   • AData analyst, because they already understand the sales data and can extend the dashboards with a forecast column.
   • BData engineer, because they own the pipelines and can add a machine-learning step to the existing data flow.
   • CData scientist, because the task requires developing a predictive model from historical data to anticipate future events.
   • DBusiness analyst, because they can interview store managers to understand ordering patterns and write a requirements document.
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2. 2foundation · easy

   How does the data scientist role apply in a big data environment?

   • ABy focusing exclusively on data storage and retrieval
   • BBy manually reviewing all data to ensure accuracy
   • CBy using advanced analytics techniques on large-scale datasets to uncover patterns and insights
   • DBy reducing the amount of data collected to simplify analysis
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4. 3foundation · easy

   Which of the following best describes the main objective of a data scientist's work?

   • ATo build and optimize data pipelines for efficient processing
   • BTo develop user interfaces for data visualization tools
   • CTo answer business questions by analyzing data and building predictive models
   • DTo ensure data is stored securely and complies with regulations
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5. 4foundation · easy

   How does a data scientist's role differ from that of a data analyst?

   • AData scientists work with data, while data analysts work with business processes
   • BData scientists are responsible for data storage, while data analysts are responsible for data visualization
   • CData scientists focus on descriptive statistics, while data analysts build predictive models
   • DData scientists use advanced modeling and machine learning, while data analysts primarily use descriptive analytics and reporting
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6. 5expert · hard

   A manufacturing company has sensors on its equipment that generate high-frequency data. The company wants to implement predictive maintenance to reduce downtime. The data science team is small, and the data engineer is already overloaded with other projects. Which approach best utilizes the data scientist's skills while minimizing dependency on the data engineer?

   • AHire a second data engineer to build the pipeline, even though the budget is tight.
   • BUse a cloud-based machine learning platform that can ingest streaming sensor data and build models with minimal infrastructure setup.
   • CHave the data analyst manually download sensor data and analyze it in Excel.
   • DWait for the data engineer to build a custom data pipeline before starting any analysis.
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