WGU D491 INTRODUCTION TO ANALYTICS OA EXAM AND
STUDY GUIDE NEWEST 2024-2025 ACTUAL EXAM 250
QUESTIONS AND CORRECT DETAILED ANSWERS (VERIFIED
ANSWERS) |ALREADY GRADED A+
Which phase of a data analytics project involves articulating findings and outcomes for stakeholders
while considering caveats, assumptions, and limitations?
Data preparation
Communicate results
Operationalize
Model development - ANSWER-Communicate results
What is the purpose of the communicate results phase in a data analytics project?
Presenting findings and outcomes to stakeholders
Preparing and managing data for analysis
Evaluating the project's financial and technical results
Creating and refining analytical models - ANSWER-Presenting findings and outcomes to stakeholders
Which activity should the data analytics team focus on during the communicate results phase
- Presenting key findings to stakeholders and evaluating the project's success
- Building and testing different predictive models for customer churn
- Analyzing the financial impact of the project on the company's revenue and customer retention
- Performing data cleaning and transforming raw data into usable formats - ANSWER-Presenting key
findings to stakeholders and evaluating the project's success
Which tools are commonly used for communicating results in data analytics projects?
- Predictive modeling software and programming languages
,- Data visualization tools and presentation software
- Database management systems and data warehouses
- Text editors and spreadsheet software - ANSWER-Data visualization tools and presentation software
What do data analytics teams do in the operationalize phase of a data analytics project?
- Apply data transformations to fix problems with data and surface information
- Communicate project benefits, set up the pilot project, and deploy in production
- Explore data, create model sets, and partition them into training, validation, and test sets
- Translate business problems into data mining problems and locate appropriate data - ANSWER-
Communicate project benefits, set up the pilot project, and deploy in production
What is the primary purpose of the operationalize phase in a data analytics project?
- To pilot the model, refine it, and fully deploy it
- To develop and train various data models
- To prepare and clean the data for analysis
- To explore data and partition it into training, validation, and test sets - ANSWER-To pilot the model,
refine it, and fully deploy it
What should business users and project sponsors do with their findings during the operationalize phase
of a data analytics project?
- Develop and refine data models
- Assess benefits, implications, and business impact
- Produce detailed reports and visuals
- Evaluate project completion and goals - ANSWER-Assess benefits, implications, and business impact
,What should analysts do with the findings discovered during the operationalize phase of a data analytics
project?
- Assess project risks and return on investment (ROI)
- Create technical specifications
- Evaluate the project's success
- Modify reports and dashboards - ANSWER-Modify reports and dashboards
A company recently completed a data analytics project to identify the most energy-efficient products to
add to the catalog. The project team comprised business users, project sponsors, analysts, data
scientists, data engineers, and database administrators. Now, the team needs to share their findings with
various stakeholders. What should the data scientists, data engineer, and database administrator do to
share their findings?
- Share code and provide implementation details
- Manage project timelines and budgets
- Assess the benefits and implications of findings
- Create high-level presentations - ANSWER-Share code and provide implementation details
Which type of data is needed to assess whether a new type of web content is increasing user
engagement?
Web log
Demographic
Competitor analysis
Advertising cost - ANSWER-Web log
A data analyst is tasked with creating a comprehensive report about a media company's user base for
advertisers.
Which data is most useful to include?
, Demographic
Advertiser cost
Web log
Competitor analysis - ANSWER-Demographic
A media firm is in talks with a larger conglomerate about a possible merger.
Which data is relevant for a data analyst to include in a report for its manager?
Advertiser cost
Competitor analysis
Demographic
Web log - ANSWER-Competitor Analysis
A grocery store chain collected data on customer purchases, sales transactions, and inventory levels.
Which question can a data analytics project ANSWER using descriptive analytics?
- What is the optimal inventory level for each product?
- Are there segments of customers whose purchase habits differ during the week compared to the
weekend?
- What are the most popular products at each store's location?
- Can future customer purchases be predicted based on past data? - ANSWER-What are the most
popular products at each store's location?
A manufacturing company collected data on production processes, equipment downtime, and
maintenance logs.
Which question can a data analytics project ANSWER using diagnostic analytics?
- How can energy consumption be reduced during production processes without affecting product
quality?
STUDY GUIDE NEWEST 2024-2025 ACTUAL EXAM 250
QUESTIONS AND CORRECT DETAILED ANSWERS (VERIFIED
ANSWERS) |ALREADY GRADED A+
Which phase of a data analytics project involves articulating findings and outcomes for stakeholders
while considering caveats, assumptions, and limitations?
Data preparation
Communicate results
Operationalize
Model development - ANSWER-Communicate results
What is the purpose of the communicate results phase in a data analytics project?
Presenting findings and outcomes to stakeholders
Preparing and managing data for analysis
Evaluating the project's financial and technical results
Creating and refining analytical models - ANSWER-Presenting findings and outcomes to stakeholders
Which activity should the data analytics team focus on during the communicate results phase
- Presenting key findings to stakeholders and evaluating the project's success
- Building and testing different predictive models for customer churn
- Analyzing the financial impact of the project on the company's revenue and customer retention
- Performing data cleaning and transforming raw data into usable formats - ANSWER-Presenting key
findings to stakeholders and evaluating the project's success
Which tools are commonly used for communicating results in data analytics projects?
- Predictive modeling software and programming languages
,- Data visualization tools and presentation software
- Database management systems and data warehouses
- Text editors and spreadsheet software - ANSWER-Data visualization tools and presentation software
What do data analytics teams do in the operationalize phase of a data analytics project?
- Apply data transformations to fix problems with data and surface information
- Communicate project benefits, set up the pilot project, and deploy in production
- Explore data, create model sets, and partition them into training, validation, and test sets
- Translate business problems into data mining problems and locate appropriate data - ANSWER-
Communicate project benefits, set up the pilot project, and deploy in production
What is the primary purpose of the operationalize phase in a data analytics project?
- To pilot the model, refine it, and fully deploy it
- To develop and train various data models
- To prepare and clean the data for analysis
- To explore data and partition it into training, validation, and test sets - ANSWER-To pilot the model,
refine it, and fully deploy it
What should business users and project sponsors do with their findings during the operationalize phase
of a data analytics project?
- Develop and refine data models
- Assess benefits, implications, and business impact
- Produce detailed reports and visuals
- Evaluate project completion and goals - ANSWER-Assess benefits, implications, and business impact
,What should analysts do with the findings discovered during the operationalize phase of a data analytics
project?
- Assess project risks and return on investment (ROI)
- Create technical specifications
- Evaluate the project's success
- Modify reports and dashboards - ANSWER-Modify reports and dashboards
A company recently completed a data analytics project to identify the most energy-efficient products to
add to the catalog. The project team comprised business users, project sponsors, analysts, data
scientists, data engineers, and database administrators. Now, the team needs to share their findings with
various stakeholders. What should the data scientists, data engineer, and database administrator do to
share their findings?
- Share code and provide implementation details
- Manage project timelines and budgets
- Assess the benefits and implications of findings
- Create high-level presentations - ANSWER-Share code and provide implementation details
Which type of data is needed to assess whether a new type of web content is increasing user
engagement?
Web log
Demographic
Competitor analysis
Advertising cost - ANSWER-Web log
A data analyst is tasked with creating a comprehensive report about a media company's user base for
advertisers.
Which data is most useful to include?
, Demographic
Advertiser cost
Web log
Competitor analysis - ANSWER-Demographic
A media firm is in talks with a larger conglomerate about a possible merger.
Which data is relevant for a data analyst to include in a report for its manager?
Advertiser cost
Competitor analysis
Demographic
Web log - ANSWER-Competitor Analysis
A grocery store chain collected data on customer purchases, sales transactions, and inventory levels.
Which question can a data analytics project ANSWER using descriptive analytics?
- What is the optimal inventory level for each product?
- Are there segments of customers whose purchase habits differ during the week compared to the
weekend?
- What are the most popular products at each store's location?
- Can future customer purchases be predicted based on past data? - ANSWER-What are the most
popular products at each store's location?
A manufacturing company collected data on production processes, equipment downtime, and
maintenance logs.
Which question can a data analytics project ANSWER using diagnostic analytics?
- How can energy consumption be reduced during production processes without affecting product
quality?
