NEW DA0-002 BRAINDUMPS QUESTIONS & LATEST DA0-002 EXAM PATTERN

New DA0-002 Braindumps Questions & Latest DA0-002 Exam Pattern

New DA0-002 Braindumps Questions & Latest DA0-002 Exam Pattern

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Tags: New DA0-002 Braindumps Questions, Latest DA0-002 Exam Pattern, Study DA0-002 Demo, Reliable Test DA0-002 Test, DA0-002 Reliable Test Prep

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Latest DA0-002 Exam Pattern | Study DA0-002 Demo

Nowadays everyone is interested in the field of CompTIA because it is growing rapidly day by day. The CompTIA Data+ Exam (2025) (DA0-002) credential is designed to validate the expertise of candidates. But most of the students are confused about the right preparation material for DA0-002 Exam Dumps and they couldn't find real DA0-002 exam questions so that they can pass CompTIA DA0-002 certification exam in a short time with good grades.

CompTIA Data+ Exam (2025) Sample Questions (Q99-Q104):

NEW QUESTION # 99
Which of the following data repositories stores unaltered data?

  • A. Data warehouse
  • B. Data lake
  • C. Data factory
  • D. Data table

Answer: B

Explanation:
This question falls under theData Concepts and Environmentsdomain, focusing on data repositories. The task is to identify a repository that stores data in its original, unaltered form.
* Data lake (Option A): A data lake stores raw, unaltered data in its native format (structured, semi- structured, or unstructured), making it the correct choice.
* Data warehouse (Option B): A data warehouse stores processed, structured data, often transformed for analysis, not unaltered.
* Data table (Option C): A data table is a structure within a database, not a repository, and may contain altered data.
* Data factory (Option D): A data factory (e.g., Azure Data Factory) is a data integration service, not a repository for storing data.
The DA0-002 Data Concepts and Environments domain includes understanding "different types of databases and data repositories," and a data lake is designed to store unaltered data.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 100
Which of the following best describes the method used to combine files, software, and libraries for use on various operating systems and environments?

  • A. Virtual machine
  • B. Containerization
  • C. Code repository
  • D. Package manager

Answer: B

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 # 101
A data analyst encounters an issue with new software and a code that they are using. The analyst includes print statements in the code to try to identify the issue, without success. An informal peer review of the code also produces the same result. The analyst confirms that the software is updated to the latest version and compatible with the code. Which of the following troubleshooting steps should the analyst take next?

  • A. Use the old software and preexisting code, since both were functional.
  • B. Research the issue online and see if a solution is available.
  • C. Escalate to the department manager and ask for assistance.
  • D. Contact the IT department and inform them that the software has a bug.

Answer: B

Explanation:
This question pertains to theData Governancedomain, focusing on troubleshooting andmaintaining data quality in software processes. The analyst has already tried basic debugging and confirmed compatibility, so the next step involves seeking external resources.
* Use the old software and preexisting code, since both were functional (Option A): Reverting to old software avoids solving the issue and may introduce other risks (e.g., security vulnerabilities).
* Contact the IT department and inform them that the software has a bug (Option B): Assuming a bug without further investigation is premature, especially since compatibility was confirmed.
* Escalate to the department manager and ask for assistance (Option C): Escalation is a later step after exhausting technical troubleshooting options.
* Research the issue online and see if a solution is available (Option D): Researching online (e.g., forums, documentation) is a logical next step to find solutions or identify known issues, especially after local debugging fails.
The DA0-002 Data Governance domain includes "data quality control concepts," and researching online is a standard troubleshooting step to maintain data process integrity.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.


NEW QUESTION # 102
Which of the following best describes the reason an analyst would reference a data dictionary versus a source's metadata?

  • A. To find a summary of basic information about the dataset
  • B. To gather information about the availability of the data
  • C. To find the content and specific attributes for a dataset
  • D. To gather information and resources about the data

Answer: C

Explanation:
This question is part of theData Concepts and Environmentsdomain, focusing on the purpose of data documentation tools like data dictionaries and metadata. The question compares their uses.
* To gather information and resources about the data (Option A): This is too vague and not specific to a data dictionary's purpose.
* To find the content and specific attributes for a dataset (Option B): A data dictionary provides detailed definitions of data elements (e.g., field names, types, descriptions), which is more specific than metadata, which often includes broader information like creation date or source.
* To find a summary of basic information about the dataset (Option C): This better describes metadata, which provides high-level summaries, not detailed attributes.
* To gather information about the availability of the data (Option D): Neither a data dictionary nor metadata typically focuses on data availability.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and a data dictionary is specifically used to find detailed attributes of a dataset.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 103
Which of the following is the most efficient to use when programming repeatable tasks?

  • A. RPA
  • B. Deep learning
  • C. NLP
  • D. LLM

Answer: A

Explanation:
This question pertains to theData Acquisition and Preparationdomain, focusing on tools for automating repeatable tasks in data processes. The task is to identify the most efficient programming method.
* LLM (Option A): Large Language Models (e.g., GPT) are for text generation, not efficient for repeatable data tasks.
* Deep learning (Option B): Deep learning is for complex pattern recognition (e.g., image classification), not efficient for simple repeatable tasks.
* NLP (Option C): Natural Language Processing is for text analysis, not general repeatable tasks.
* RPA (Option D): Robotic Process Automation (RPA) automates repetitive, rule-based tasks (e.g., data entry, file processing), making it the most efficient for programming repeatable tasks.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and RPA is a widely used method for automating repeatable data tasks.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.


NEW QUESTION # 104
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