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DA0-002 Latest Exam Materials | Answers DA0-002 Real Questions

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CompTIA Data+ Exam (2025) Sample Questions (Q41-Q46):

NEW QUESTION # 41
Which of the following best describes an assessment a data analyst would use to validate that the number of records in a dataset matches the expected results?

A. Unit test
B. Stress test
C. Source control
D. Health check

Answer: A

Explanation:
This question pertains to theData Governancedomain, focusing on data quality validation techniques. The task is to validate that the number of records matches expectations, which requires a specific type of assessment.
* Source control (Option A): Source control (e.g., Git) manages code versions, not dataset validation.
* Unit test (Option B): A unit test checks a specific component of a process, such as verifying that the number of records in a dataset matches the expected count, making it the best fit.
* Stress test (Option C): Stress tests evaluate system performance under load, not record counts.
* Health check (Option D): A health check monitors system status but isn't specific to validating record counts.
The DA0-002 Data Governance domain includes "data quality control concepts," and unit tests are a standard method for validating specific data outcomes like record counts.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 42
An analyst is building a reporting deck. The deck must include tracking and visualizing metrics and row-level security. Which of the following actions should the analyst take after meeting all of the requirements?

A. Explain the desired level of reporting detail.
B. Present an analysis of the data.
C. Find out the project due date.
D. Show a mock-up to the team.

Answer: D

Explanation:
This question pertains to theVisualization and Reportingdomain, focusing on the process of building a reporting deck. After meeting requirements (tracking metrics, visualizing data, and row-level security), the next step involves validation with stakeholders.
* Show a mock-up to the team (Option A): Creating a mock-up and presenting it to the team ensures alignment on design and functionality before finalizing, which is a standard next step in report development.
* Explain the desired level of reporting detail (Option B): This should have been done earlier during requirements gathering, not after meeting them.
* Present an analysis of the data (Option C): Data analysis might inform the deck, but the task focuses on building the deck, not presenting analysis.
* Find out the project due date (Option D): The due date should have been established earlier in the project planning phase.
The DA0-002 Visualization and Reporting domain includes "translating business requirements to form the appropriate visualization," and showing a mock-up ensures the reporting deck meets stakeholder expectations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.

NEW QUESTION # 43
A data analyst receives a new data source that contains employee IDs, job titles, dates of birth, addresses, years of service, and employees' birth months. Which of the following inconsistencies should the analyst identify?

A. Redundancy
B. Parallel
C. Equivalence
D. Duplication

Answer: A

Explanation:
This question falls under theData Governancedomain, focusing on identifying data quality issues. The dataset includes dates of birth and birth months, which suggests a potential inconsistency.
* Redundancy (Option A): The dataset includes both dates of birth (e.g., 1990-05-15) and birth months (e.g., May), which is redundant because the birth month can be derived from the date of birth, indicating a data quality issue.
* Equivalence (Option B): Equivalence isn't a standard data quality term in this context; it might refer to data matching, which isn't the issue here.
* Parallel (Option C): Parallel isn't a recognized data quality term; it might relate to processing, not data inconsistencies.
* Duplication (Option D): Duplication refers to identical records, but the issue here is redundant fields, not duplicate rows.
The DA0-002 Data Governance domain includes "data quality control concepts," and redundancy is a key inconsistency when the same information is stored in multiple forms unnecessarily.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 44
Which of the following pieces of information, if made public, results in a data privacy violation?

A. Age
B. Gender
C. Employment status
D. Driver's license

Answer: D

Explanation:
This question falls under theData Governancedomain, which in DA0-002 includes understanding data privacy and compliance with regulations like GDPR. The question asks which piece of information, if made public, constitutes a privacy violation, meaning it must be personally identifiable information (PII).
* Gender (Option A): Gender is not typically considered PII on its own, as it's not uniquely identifiable.
* Driver's license (Option B): A driver's license number is PII because it uniquely identifies an individual and can be linked to other personal information, such as name and address. Making it public violates privacy regulations.
* Age (Option C): Age alone isn't PII, as it's not uniquely identifiable.
* Employment status (Option D): Employment status (e.g., employed, unemployed) isn't PII, as it doesn't uniquely identify an individual.
The DA0-002 Data Governance domain includes "identifying PII and data privacy concepts," and a driver's license is a clear example of PII that, if exposed, results in a privacy violation.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 45
A user needs a report that shows the main causes of customer churn rate in a three-year period. Which of the following methods provides this information?

A. Predictive
B. Prescriptive
C. Inferential
D. Descriptive

Answer: D

Explanation:
This question falls under theData Analysisdomain, focusing on analytical methods for reporting. The task is to identify the causes of customer churn over three years, which involves analyzing historical data.
* Inferential (Option A): Inferential statistics make predictions or generalizations about a population, not focused on identifying causes in historical data.
* Descriptive (Option B): Descriptive analytics summarizes historical data to identify patterns and causes (e.g., reasons for churn), which fits the task.
* Prescriptive (Option C): Prescriptive analytics provides recommendations, which goes beyond identifying causes.
* Predictive (Option D): Predictive analytics forecasts future outcomes, not focused on historical causes.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and descriptive analytics is best for identifying causes in historical data.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

NEW QUESTION # 46
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