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CompTIA DA0-002 Exam Overview:

Certification Vendor:CompTIA
Exam Name:CompTIA Data+ Exam (2025)
Exam Number:DA0-002
Available Languages:English
Exam Price:USD 255
Certificate Validity Period:3 years
Exam Duration:90 minutes
Related Certifications:CompTIA Data+
Real Exam Qty:Up to 90
Passing Score:720 (scale of 100–900)
Exam Format:Performance-based, Multiple-choice
Sample Questions:CompTIA DA0-002 Sample Questions
Exam Way:Online proctored or at Pearson VUE authorized testing centers
Pre Condition:No formal prerequisites; recommended 18–24 months of experience in a report/business analyst role or equivalent knowledge
Official Syllabus URL:https://www.comptia.org/certifications/data

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CompTIA DA0-002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • This section of the exam measures skills of a Data Governance Associate and introduces principles for keeping data secure, accurate, and compliant. It covers access controls, encryption, classification of sensitive data like PII and PHI, and legal requirements tied to data use. Candidates must know how to apply quality checks, validate data, and manage master data effectively. It also addresses best practices for maintaining integrity through data dictionaries, audits, and standardisation processes.
Topic 2
  • Visualization: This section of the exam measures skills of a Data Visualisation Specialist and focuses on turning raw data into clear, visual insights. It teaches how to match visual formats like bar charts, heat maps, and line graphs to specific audiences and needs. Candidates must understand how to create dashboards and reports using proper design elements such as labels, layout, branding, and colour schemes. This section also includes best practices for dashboard development and delivery through various platforms and user access levels.
Topic 3
  • Data Mining: This section of the exam measures skills of a Business Intelligence Analyst and covers how data is collected, cleaned, and prepared for analysis. It explains methods like ETL and ELT for data integration, as well as web scraping, API use, and survey data collection. Candidates are expected to identify issues like missing or duplicated data and apply techniques like filtering, sorting, merging, and normalizing. The section also touches on query optimization strategies to improve data handling efficiency.
Topic 4
  • Data Concepts and Environments: This section of the exam measures the skills of a Junior Data Analyst and focuses on understanding core data concepts such as database types, schema structures, and data formats. It highlights differences between structured and unstructured data, compares file types like CSV, JSON, and XML, and introduces key ideas about data dimensions and slowly changing dimensions. Knowing how data is stored and organized helps professionals better prepare for analysis and reporting tasks.

CompTIA Data+ Exam Sample Questions (Q120-Q125):

NEW QUESTION # 120
A recent server migration applied an update to dataset naming conventions. Multiple users are now reporting stale information in an existing dashboard. The date in the dataset confirms a successful data refresh. Which of the following should a data analyst do first?

Answer: D


NEW QUESTION # 121
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?

Answer: B

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 # 122
A data analyst needs to create and deliver a dashboard that displays the company's financial transactions as they are updated. Which of the following delivery methods should the analyst consider? (Select two).

Answer: A,B


NEW QUESTION # 123
A data analyst receives a request for the current employee head count and runs the following SQL statement:
SELECT COUNT(EMPLOYEE_ID) FROM JOBS
The returned head count is higher than expected because employees can have multiple jobs. Which of the following should return an accurate employee head count?

Answer: D

Explanation:
This question falls under theData Analysisdomain of CompTIA Data+ DA0-002, which involves using SQL queries to analyze data and address issues like duplicates in datasets. The issue here is that the initial query counts all instances of EMPLOYEE_ID in the JOBS table, but employees can have multiple jobs, leading to an inflated head count. The goal is to count unique employees.
* SELECT JOB_TYPE, COUNT DISTINCT(EMPLOYEE_ID) FROM JOBS (Option A): This query is syntactically incorrect because COUNT DISTINCT(EMPLOYEE_ID) should use parentheses as COUNT(DISTINCT EMPLOYEE_ID). It also groups by JOB_TYPE, which is unnecessary for a total head count.
* SELECT DISTINCT COUNT(EMPLOYEE_ID) FROM JOBS (Option B): This query is incorrect because DISTINCT applies to the rows returned, not the COUNT function directly. It doesn't address the duplicate EMPLOYEE_ID issue.
* SELECT JOB_TYPE, COUNT(DISTINCT EMPLOYEE_ID) FROM JOBS (Option C): While this query correctly uses COUNT(DISTINCT EMPLOYEE_ID) to count unique employees, grouping by JOB_TYPE breaks the count into separate groups, which isn't required for a total head count.
* SELECT COUNT(DISTINCT EMPLOYEE_ID) FROM JOBS (Option D): This query correctly counts only unique EMPLOYEE_IDs by using the DISTINCT keyword within the COUNT function, providing an accurate total head count without grouping.
The DA0-002 Data Analysis domain emphasizes "given a scenario, applying the appropriate descriptive statistical methods using SQL queries," which includes handling duplicates with functions like COUNT (DISTINCT). Option D is the most direct and accurate method for a total unique head count.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 124
Which of the following best describes the method used to combine files, software, and libraries for use on various operating systems and environments?

Answer: C

Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on methods for managing software and data environments. The task is to identify a method that combines files, software, and libraries for use across different systems.
* Package manager (Option A): Package managers (e.g., npm) manage software dependencies but don't combine files and libraries for cross-system use.
* Code repository (Option B): Code repositories (e.g., GitHub) store code but don't package it for deployment across environments.
* Virtual machine (Option C): Virtual machines emulate entire operating systems, which is heavier than needed for combining files and libraries.
* Containerization (Option D): Containerization (e.g., Docker) packages files, software, and libraries into a container that can run consistently across different operating systems and environments, making it the best choice.
The DA0-002 Data Concepts and Environments domain includes understanding "data environments," and containerization is a standard method for ensuring consistency across systems.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 125
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