WGU D491 intro to data analytics Exam Latest Update 2024 171 Questions and Verified Correct Answers Guaranteed Success 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
b. Manage project tim - CORRECT ANSWER: a. Share code and provide
implementation details
A data analyst is planning a new analytics project for a retail company and needs to collect data from different sources to complete the project.Which question should be asked regarding the sources and quality of the available data for the project?
- Will the data support the hypothesis?
- What is the time frame of the data, and how often is it updated?
- Is the data being obtained from a third party, a public company, or a private
- Is the data in a .csv format or a .xls format? - CORRECT ANSWER: b. What is the
company?
time frame of the data, and how often is it updated?
A data analyst works at an e-commerce company that wants to understand its customer churn rate. Their manager has tasked them with conducting a data analytics project to identify customers at risk of churn and offer these customers targeted promotions to retain their business.What is the primary purpose of the data analytics project's results in this scenario?
- To optimize inventory management
- To identify customer preferences
- To compare the company's churn rate to industry benchmarks
d - CORRECT ANSWER: d. To predict customer churn risk
A marketing company has a client who wants to know their social media engagement for the past month. They have accounts on several social media platforms and want to compare their engagement across these platforms.Which visualization metric should be used to find the social media engagement for the client?
- Box plot
- Pie chart
- Bar graph
d. Heat map - CORRECT ANSWER: d. Heat map
How is data science different from data analytics? 1 / 4
- Data science focuses on developing new algorithms and models, while data analytics
- Data science focuses more on data visualization, while data analytics focuses on
- Data science focuses more on tracking experimental data, and data analytics is
focuses on using existing models to analyze data.
data cleaning and preprocessing.
based on statistical methods and hypotheses.
d. Data science involves creating new algorithms, w - CORRECT ANSWER: a. Data
science focuses on developing new algorithms and models, while data analytics focuses on using existing models to analyze data.
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
d. Evaluate project completion and goals - CORRECT ANSWER: b. Assess benefits,
implications, and business impact
Which activities should be the focus of the model planning phase?
- Transforming data to bring information to the surface
- Visualizing and exploring data patterns
- Cleaning and conditioning data for analysis
- Partitioning the data into training, validation, and test sets - CORRECT ANSWER: d.
Partitioning the data into training, validation, and test sets
Which information tool is a possible source of data in a data analytics project?
- Company logo designs
- Consumer perception survey questions
- Marketing slogans
d. Corporate information system - CORRECT ANSWER: dd. Corporate information
system
Why is a project sponsor a key stakeholder in a data analytics project?
- They ensure that the project aligns with business goals and objectives.
- They provide funding for the project.
- They are the primary users of the project's outputs.
d. They are responsible for implementing the project. - CORRECT ANSWER: a. They
ensure that the project aligns with business goals and objectives.A business seeks to increase profitability and optimize inventory management. They decide to carry out data analytics research to determine which merchandise is selling quickly and which is selling slowly. The research seeks to determine whether there is a relationship between the kind of merchandise and sales velocity.Which data is required to answer the question for the data analytics project in the scenario?-Sales data categorized by customer segment -Sales data categorized by region -Sales data categorized by time period 2 / 4
-Sales data categorized by product - CORRECT ANSWER: Sales data categorized by
product
A car manufacturing company is looking to improve its production by analyzing how factors such as temperature, humidity, and machine performance affect production efficiency. To identify the key factor that affects efficiency the most, an analyst uses the regression analysis technique.What justifies the use of regression analysis for the given
task? - CORRECT ANSWER: Regression analysis is used to analyze the relationship
between one or more independent variables and a dependent variable.
A company in the renewable energy industry is working on a data analytics project to identify which areas are more likely to adopt solar power. The data science team needs to gather relevant data sources for this project.
Which data sources are most relevant for a renewable energy company looking to identify areas more likely to adopt solar power?-Medical insurance claims data, survey response data, and warranty claims data -Web log data, e-commerce server application logs, and call-center records -Point-of- sale data, credit card charge records, and telephone call detail records -Census and economic data, hourly weather readings, and demographic data -
CORRECT ANSWER: Census and economic data, hourly weather readings, and
demographic data (Census data, economic data, hourly weather readings, and demographic data can provide valuable insights into geographic areas, financial capacity, and environmental factors that can influence the adoption of solar power.)
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 -Assess the benefits and implications of findings -Create high-level presentations
-Manage project timelines and budgets - CORRECT ANSWER: Share code and provide
implementation details (Data scientists, data engineers, and database administrators share their code and create technical documents on how to implement it.)
A company wants to predict the likelihood of a customer responding to a marketing campaign. The data set contains both numerical and categorical variables.Which analytics technique should the company use?-Random forest -Principal component analysis (PCA) -K-means clustering -Logistic regression - CORRECT ANSWER: Logistic regression (Logistic regression is a suitable technique for binary classification problems, such as predicting the likelihood of 3 / 4
a customer responding to a marketing campaign when the dataset contains numerical and categorical variables.)
A company will survey its customers to understand the potential demand for a new product. A data analyst will review the data.Which question should the analysis consider
to validate the representativity of the data? - CORRECT ANSWER: What is the
response rate of the survey?
A data analyst at a retail company is provided with a large dataset containing sales transactions, customer information, and product details. The analyst is tasked with preparing the data for analysis and modeling.Which activity would the analyst perform during the data preparation phase?-Exploring available data to understand its characteristics and suitability -Identifying the business problem or research question that needs to be addressed -Developing initial hypotheses about the relationship between data variables -Allocating computing resources for the data analysis - CORRECT ANSWER: Exploring available data to understand its characteristics and suitability
A data analyst for a retail company has collected data on customer demographics, purchase history, and marketing campaigns.Which data analytic technique should be used to predict demand for the upcoming holiday season?-Use a machine learning algorithm to predict future demand and determine the reorder quantity for each product.-Use an experiment to see whether consumers prefer music in the store while they shop.-Use clustering to divide customers into high-spending and low-spending groups.-Use text mining to extract which product descriptions have the most positive sentiments. - CORRECT ANSWER: Use a machine learning algorithm to predict future demand and determine the reorder quantity for each product. (This approach considers historical sales data and other relevant external factors such as seasonality, trends, and economic indicators to predict future demand accurately. The predicted demand can then determine the optimal reorder quantity for each product, thereby optimizing inventory management.)
A data analyst is analyzing the employees' salaries at a company to find a representative value that summarizes the central tendency of the data.Which metric should be used to summarize the central tendency of the data? -Standard deviation -Mode -Range
-Median - CORRECT ANSWER: Median (The median is the middle value in a dataset
when the data is arranged in order. It is an appropriate metric for summarizing the central tendency of the data in this scenario, as it provides information on the typical salary of employees. The median is less sensitive to outliers than the mean and
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