Get All CompTIA DataX Certification Exam Questions with Validated Answers
Vendor:
CompTIA
Exam Code:
DY0-001
Exam Name:
CompTIA DataX Certification Exam
Exam Questions:
85
Last Updated:
February 5, 2026
Related Certifications:
CompTIA DataX
Exam Tags:
ExpertData ScientistsMachine Learning Engineers
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Free CompTIA DY0-001 Exam Actual Questions
Question No. 1
A data scientist wants to predict a person's travel destination. The options are:
Which of the following models would best fit this use case?
You need a supervised multiclass classification model to predict one of the four labeled destinations. Linear Discriminant Analysis is designed for such tasks, finding the linear boundaries that best separate the known destination classes.
Question No. 2
Which of the following best describes the minimization of the residual term in a ridge linear regression?
Ridge regression extends ordinary least squares by adding an L2 penalty on the coefficients, but it still minimizes the sum of squared residuals (e) as its loss term.
Question No. 3
A data scientist needs to analyze a company's chemical businesses and is using the master database of the conglomerate company. Nothing in the data differentiates the data observations for the different businesses. Which of the following is the most efficient way to identify the chemical businesses' observations?
Engaging the business team leverages domain expertise to pinpoint which records pertain to chemical operations, allowing you to extract and analyze just the relevant subset. This avoids the time and resource waste of ingesting and sifting through unrelated data.
Question No. 4
A data scientist is presenting the recommendations from a monthslong modeling and experiment process to the company's Chief Executive Officer. Which of the following is the best set of artifacts to include in the presentation?
Executive audiences need concise, high-level insights: what you found (results), what you suggest (recommendations), why it matters (justifications), and visual summaries (clear charts). Detailed methods, code, or raw data aren't appropriate at the C-suite level.
Question No. 5
A data scientist is preparing to brief a non-technical audience that is focused on analysis and results. During the modeling process, the data scientist produced the following artifacts:
Which of the following artifacts should the data scientist include in the briefing? (Choose two.)
For a nontechnical audience centered on results, polished visualizations (charts and dashboards) and clear, high-level performance metrics (accuracy, precision, recall, F1 score) best convey the key takeaways. The deeper technical details, code docs, data dictionaries, and algorithm math, should be omitted at this level.
