CompTIA DY0-001 - CompTIA DataX Exam
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Total 83 questions
Question #6 (Topic: Exam A)
Which of the following modeling tools is appropriate for solving a scheduling problem?
A. One-armed bandit
B. Constrained optimization
C. Decision tree
D. Gradient descent
Answer: B
Question #7 (Topic: Exam A)
Which of the following environmental changes is most likely to resolve a memory constraint error when running a complex model using distributed computing?
A. Converting an on-premises deployment to a containerized deployment
B. Migrating to a cloud deployment
C. Moving model processing to an edge deployment
D. Adding nodes to a cluster deployment
Answer: D
Question #8 (Topic: Exam A)
A data analyst wants to save a newly analyzed data set to a local storage option. The data set must meet the following requirements:
Be minimal in size
Have the ability to be ingested quickly
Have the associated schema, including data types, stored with it
Which of the following file types is the best to use?
Be minimal in size
Have the ability to be ingested quickly
Have the associated schema, including data types, stored with it
Which of the following file types is the best to use?
A. JSON
B. Parquet
C. XML
D. CSV
Answer: B
Question #9 (Topic: Exam A)
Which of the following is a key difference between KNN and k-means machine-learning techniques?
A. KNN operates exclusively on continuous data, while k-means can work with both continuous and categorical data.
B. KNN performs better with longitudinal data sets, while k-means performs better with survey data sets.
C. KNN is used for finding centroids, while k-means is used for finding nearest neighbors.
D. KNN is used for classification, while k-means is used for clustering.
Answer: D
Question #10 (Topic: Exam A)
A data scientist needs to:
Build a predictive model that gives the likelihood that a car will get a flat tire.
Provide a data set of cars that had flat tires and cars that did not.
All the cars in the data set had sensors taking weekly measurements of tire pressure similar to the sensors that will be installed in the cars consumers drive. Which of the following is the most immediate data concern?
Build a predictive model that gives the likelihood that a car will get a flat tire.
Provide a data set of cars that had flat tires and cars that did not.
All the cars in the data set had sensors taking weekly measurements of tire pressure similar to the sensors that will be installed in the cars consumers drive. Which of the following is the most immediate data concern?
A. Granularity misalignment
B. Multivariate outliers
C. Insufficient domain expertise
D. Lagged observations
Answer: D
