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CompTIA Data+ Exam (2025) Sample Questions (Q75-Q80):

NEW QUESTION # 75
A developer builds an online survey that requires all questions to have an answer. Which of the following inconsistencies does this setting prevent?

A. Data corruption
B. Missing values
C. Completeness
D. Duplication

Answer: B

Explanation:
This question pertains to theData Governancedomain, focusing on data quality and consistency in survey design. Requiring all questions to have an answer ensures a specific type of data quality.
* Missing values (Option A): Requiring answers prevents missing values (NULLs or blanks) in the survey responses, which is the primary inconsistency this setting addresses.
* Duplication (Option B): Duplication refers to repeated records, not prevented by requiring answers.
* Data corruption (Option C): Data corruption involves damaged or altered data, not related to missing answers.
* Completeness (Option D): Completeness is the concept of having all necessary data, but "missing values" is the specific inconsistency prevented here.
The DA0-002 Data Governance domain includes "data quality control concepts," and preventing missing values ensures data integrity in survey responses.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 76
A data analyst needs to get an accurate idea of how data components are automated. Which of the following types of documentation should the analyst review first?

A. Data flow diagram
B. Data explainability report
C. Data dictionary
D. Data lineage

Answer: A

Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on documentation for understanding data processes. The analyst needs to understand automation of data components, which involves data movement and processes.
* Data flow diagram (Option A): A data flow diagram (DFD) visualizes how data moves through systems, including automated processes, making it the best starting point.
* Data explainability report (Option B): This is related to AI/ML model transparency, not data automation.
* Data dictionary (Option C): A data dictionary defines data elements, not how they're automated.
* Data lineage (Option D): Data lineage tracks data origin and transformations but doesn't focus on automation processes.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and a data flow diagram is key for visualizing automation.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

NEW QUESTION # 77
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. Stress test
B. Health check
C. Unit test
D. Source control

Answer: C

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 # 78
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. Find out the project due date.
B. Present an analysis of the data.
C. Explain the desired level of reporting detail.
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 # 79
A data analyst calculated the average score per student without making any changes to the following table:
Student
Subject
Score
123
Math
100
123
Biology
80
234
Math
96
123
Biology
80
345
Biology
88
234
Math
96
Which of the following exploration techniques should the analyst have considered before calculating the average?

A. Grouping
B. Binning
C. Duplication
D. Redundancy

Answer: C

Explanation:
This question pertains to theData Governancedomain, focusing on data quality issues that affect analysis.
The table contains duplicate rows, which would skew the average score calculation if not addressed.
* Student 123: Math (100), Biology (80), Biology (80)- Duplicate Biology score.
* Student 234: Math (96), Math (96)- Duplicate Math score.
* Student 345: Biology (88)- No duplicates.
* Duplication (Option A): The table has duplicate rows (e.g., Student 123's Biology score of 80 appears twice), which would inflate the average if not removed. The analyst should have checked for duplicates before calculating the average.
* Redundancy (Option B): Redundancy refers to unnecessary fields (e.g., storing the same data in multiple columns), not duplicate rows.
* Binning (Option C): Binning groups data into categories, not relevant for addressing duplicates in averaging.
* Grouping (Option D): Grouping (e.g., GROUP BY in SQL) might be part of the solution,but the issue to identify is duplication.
The DA0-002 Data Governance domain includes "data quality control concepts," and checking for duplication is critical to ensure accurate calculations like averages.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 80
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DA0-002 Pass4sure Exam Prep | DA0-002 Latest Exam Price

DA0-002 Latest Exam Price & New DA0-002 Test Review

CompTIA Data+ Exam (2025) Sample Questions (Q75-Q80):

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