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WGU D491 UPDATED ACTUAL Exam Questions and CORRECT Answers

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WGU D491 UPDATED ACTUAL Exam Questions and CORRECT Answers Which role in a data analytics project provides expertise for analytical techniques? Data engineer Business intelligence analyst Data scientist Database administrator - CORRECT ANSWER - Data scientist Which skills are required by data scientists for converting unstructured data to structured d

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WGU D491 UPDATED ACTUAL Exam
Questions and CORRECT Answers
Which role in a data analytics project provides expertise for analytical techniques?


Data engineer
Business intelligence analyst
Data scientist

Database administrator - CORRECT ANSWER - Data scientist


Which skills are required by data scientists for converting unstructured data to structured data in
data analytics projects?


Data visualization skills
Data wrangling skills
Text mining skills

Machine learning skills - CORRECT ANSWER - Data wrangling skills


Which skill must a business intelligence analyst possess to collect and organize data?


Data preparation
Data visualization
Data modeling

Machine learning - CORRECT ANSWER - Data preparation


What is a skill required of a data engineer?


Creating data visualizations

, Maintaining databases
Training machine learning models

Writing programs that perform data analysis - CORRECT ANSWER - Maintaining
databases


Which group of stakeholders comprises the professionals, such as line managers?


Database administrators
Data engineers
Project sponsors

Business users - CORRECT ANSWER - Business users


Which stakeholder is primarily responsible for ensuring the desired quality of the project?


Business intelligence analysts
Business users
Project managers

Project sponsors - CORRECT ANSWER - Project managers


Who offers suggestions on ideas to test as the team formulates hypotheses during the discovery
phase of a data analytics project?


Data scientists
Data visualization specialists
Project managers

Marketing experts - CORRECT ANSWER - Data scientists


Which task is typically performed to handle outliers during the data preparation phase?

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