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CompTIA Data+ Exam (2025) Sample Questions (Q102-Q107):

NEW QUESTION # 102
A data analyst needs to modify a dashboard that was created by another employee. Upon opening the dashboard, the analyst notices that the information is not loading properly. Which of the following should the analyst do to troubleshoot this error?

A. Review the data layer and data source.
B. Validate that the database is up-to-date.
C. Check that the program is updated to the latest version.
D. Ensure the correct filters are displaying on the dashboard.

Answer: A

Explanation:
This question falls under theData Governancedomain of CompTIA Data+ DA0-002, focusing on troubleshooting data quality issues in dashboards. The dashboard isn't loading properly, indicating a potential issue with the data connection or configuration.
* Review the data layer and data source (Option A): The data layer (e.g., queries, connections) and data source (e.g., database) are the foundation of a dashboard. If the information isn't loading, the issue likely lies in the data connection or query configuration, making this the first step.
* Validate that the database is up-to-date (Option B): While this might be a subsequent step, it assumes the connection is working, which should be confirmed first.
* Check that the program is updated to the latest version (Option C): Software updates might fix bugs, but this isn't the most immediate cause of data not loading.
* Ensure the correct filters are displaying on the dashboard (Option D): Filters affect data display, but if the data isn't loading at all, the issue is more fundamental.
The DA0-002 Data Governance domain includes "data quality control concepts," and reviewing the data layer and source is the primary step in troubleshooting dashboard loading issues.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 103
A data analyst receives four files that need to be unified into a single spreadsheet for further analysis. All of the files have the same structure, number of columns, and field names, but each file contains different values.
Which of the following methods will help the analyst convert the files into a single spreadsheet?

A. Clustering
B. Merging
C. Appending
D. Parsing

Answer: C

Explanation:
This question is part of theData Acquisition and Preparationdomain, which involves combining data from multiple sources. The files have the same structure but different values, meaning theyneed to be stacked vertically into one dataset.
* Merging (Option A): Merging typically involves joining datasets on a common key (e.g., a customer ID), which isn't indicated here since the files only differ in values, not keys.
* Appending (Option B): Appending stacks datasets vertically, combining rows from files with the same structure into a single dataset, which matches the scenario.
* Parsing (Option C): Parsing involves breaking down data (e.g., splitting text), not combining files.
* Clustering (Option D): Clustering is a machine learning technique for grouping similar data points, not for combining files.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as appending datasets with identical structures.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.

NEW QUESTION # 104
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 lineage
B. Data dictionary
C. Data explainability report
D. Data flow diagram

Answer: D

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 # 105
Which of the following is the most efficient to use when programming repeatable tasks?

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

Answer: B

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 # 106
A company's entire server environment is located at the company's headquarters. Which of the following describes this type of environment?

A. On-premises
B. Cloud
C. Public
D. Hybrid

Answer: A

Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on types of server environments. The servers are located at the company's headquarters, indicating a specific deployment model.
* Cloud (Option A): Cloud environments are hosted off-site by third-party providers, not at headquarters.
* On-premises (Option B): On-premises environments are located at the company's physical location (e.
g., headquarters), which matches the scenario.
* Public (Option C): Public environments are cloud-based and shared across multiple organizations, not located at headquarters.
* Hybrid (Option D): Hybrid environments combine on-premises and cloud, but the scenario specifies all servers are at headquarters.
The DA0-002 Data Concepts and Environments domain includes understanding "data environments," and on- premises describes a server environment located at the company's site.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

NEW QUESTION # 107
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