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CompTIA Data+ Exam (2025) DA0-002 Exam

Attempt the CompTIA Data+ practice test and solve real exam-like DA0-002 questions to prepare efficiently and increase your chances of success. Our CompTIA DA0-002 practice questions match the actual CompTIA Data+ Exam (2025) exam format, helping you enhance confidence and improve performance. With our DA0-002 practice exam software, you can analyze your performance, identify weak areas, and work on them effectively to boost your final CompTIA Data+ exam score.

Vendor:	CompTIA
Exam Name:	CompTIA Data+ Exam (2025)
Registration Code:	DA0-002
Related Certification:	CompTIA Data+ Certification
Exam Track:	Data analysis certifications
Exam Audience:	CompTIA Data Analysts, Reporting Analysts,

Total Questions

121

Last Updated

12-07-2026

Exam Duration

90 MINUTES

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Question: 1

A company wants to limit an employee's access to a production environment. Which of the following access control practices is the best to implement?

AMandatory

BTime-based

CAttribute-based

DRole-based

Answer: D

Explanation:

This question falls under the Data Governance domain, focusing on access control practices for data security. The task is to limit an employee's access to a production environment, requiring a structured approach.

Mandatory (Option A): Mandatory access control (MAC) uses strict, system-enforced rules (e.g., military settings), but it's overly rigid for most companies.

Time-based (Option B): Time-based access limits access to specific times, which doesn't address general production environment access.

Attribute-based (Option C): Attribute-based access control (ABAC) uses attributes (e.g., department, location), but it's complex and not the simplest solution.

Role-based (Option D): Role-based access control (RBAC) assigns permissions based on the employee's role, ensuring they only access what's needed for their job, making it the best practice for limiting production access.

The DA0-002 Data Governance domain includes 'data privacy concepts,' and role-based access control is a widely adopted practice for limiting access in production environments.

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Question: 2

Which of the following data repositories stores unstructured and structured data?

AData store

BData silo

CData mart

DData lake

Answer: D

Explanation:

This question falls under the Data Concepts and Environments domain of CompTIA Data+ DA0-002, which involves understanding different types of data repositories and their characteristics. The task is to identify a repository that can store both unstructured and structured data.

Data store (Option A): A data store is a general term for any data repository, but it's not specific enough to confirm it stores both unstructured and structured data.

Data silo (Option B): A data silo is an isolated data repository, often structured, and not typically designed for unstructured data.

Data mart (Option C): A data mart is a subset of a data warehouse, focused on structured data for specific business areas, not unstructured data.

Data lake (Option D): A data lake is a centralized repository that stores raw data in its native format, including both structured (e.g., tables) and unstructured (e.g., text, images) data, making it the correct choice.

The DA0-002 Data Concepts and Environments domain includes understanding 'different types of databases and data repositories,' and a data lake is specifically designed to handle both unstructured and structured data.

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Question: 3

A data analyst is creating a new dataset that involves bringing together the following datasets:

Name

Date of birth

Frank

23525

3/19

Martha

11290

6/13

Ellen

12141

11/4

Address

City

State

23525

1234 Harding

Chicago

11040

935 Terrace Hills

Chino

11290

2 Speedway

Miami

Which of the following would be the output if the data analyst does a FULL JOIN?

Name

Date of birth

Address

City

State

Frank

23525

3/19

1234 Harding

Chicago

Martha

11290

6/13

935 Terrace Hills

Chino

Ellen

12141

11/4

2 Speedway

Miami

Name

Date of birth

Address

City

State

Frank

23525

3/19

1234 Harding

Chicago

Martha

11290

6/13

935 Terrace Hills

Chino

Ellen

12141

11/4

2 Speedway

Miami

Name

Date of birth

Address

City

State

Frank

23525

3/19

1234 Harding

Chicago

Martha

11290

6/13

2 Speedway

Miami

Ellen

12141

11/4

935 Terrace Hills

Chino

Name

Date of birth

Address

City

State

Frank

23525

3/19

1234 Harding

Chicago

Martha

11290

6/13

2 Speedway

Miami

Ellen

12141

11/4

11040

935 Terrace Hills

Chino

AOption A

BOption B

COption C

DOption D
Explanation:

This question falls under the Data Concepts and Environments domain, focusing on database operations like joins. A FULL JOIN combines all rows from both tables, including matches and non-matches, filling in NULLs where there's no corresponding data.
The first table has IDs: 23525 (Frank), 11290 (Martha), 12141 (Ellen).
The second table has IDs: 23525, 11040, 11290.
A FULL JOIN includes all IDs: 23525, 11290, 12141, 11040.
23525 matches (Frank with 1234 Harding, Chicago, IL).
11290 matches (Martha with 2 Speedway, Miami, FL).
12141 has no match in the second table, so Address, City, and State are NULL.
11040 has no match in the first table, so Name and Date of birth are NULL.
Option A: Incorrect; it includes a row for Ellen with '2 Speedway,' but Ellen's ID (12141) doesn't match any address, and 11040 is missing.
Option B: Identical to Option A, so incorrect for the same reasons.
Option C: Incorrect; it mismatches addresses (e.g., Ellen with 935 Terrace Hills, which belongs to 11040).
Option D: Correct; it includes all IDs, with NULLs for non-matching rows (Ellen has no address, and 11040 has no name).
The DA0-002 Data Concepts and Environments domain includes understanding 'data schemas and dimensions,' such as performing joins in relational databases.

Answer: D

Explanation:

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Question: 4

Which of the following best describes a characteristic of a Boolean?

AMust be a character

BMust be two values only

CMust be numeric

DMust be system-created

Answer: B

Question: 5

A data analyst is gathering data from multiple tables in a database. The analyst needs certain columns from each table. Which of the following is the best method to accomplish this task?

AAggregate

BUnion

CNest

DJoin

Answer: D

Explanation:

This question falls under the Data Acquisition and Preparation domain, focusing on combining data from multiple tables. The analyst needs specific columns from each table, suggesting a method to combine data horizontally based on relationships.

Aggregate (Option A): Aggregation (e.g., SUM, COUNT) summarizes data, not suitable for combining columns from tables.

Union (Option B): Union stacks tables vertically, requiring identical structures, but the analyst needs specific columns, likely based on relationships, not a vertical stack.

Nest (Option C): Nesting is used for hierarchical data (e.g., JSON), not for combining relational tables.

Join (Option D): A join (e.g., INNER JOIN) combines tables horizontally based on a common key, allowing the analyst to select specific columns from each table, which fits the task.

The DA0-002 Data Acquisition and Preparation domain includes 'executing data manipulation,' and joining tables is the best method for combining specific columns from multiple tables.

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