[Q63-Q78] 合格させちゃうCompTIA Data+ DA0-002試験簡単かつ正確なPDF問題 [2026年01月15日]

合格させちゃうCompTIA Data+ DA0-002試験簡単かつ正確なPDF問題 [2026年01月15日]

DA0-002認証試験問題集解答を提供しています

質問 # 63
Which of the following AI types is the best option for time-series forecasting?

• A. Foundational models
• B. Robotic process automation
• C. Natural language processing
• D. Generative AI

正解：A

解説：
Foundational models are large AI models trained on vast amounts of data, often exhibiting strong generalization capabilities. While not specifically architected for time-series, their ability to learn complex patterns could potentially be leveraged for forecasting tasks through fine-tuning or specialized architectures built upon them.
In reality, the best AI types specifically designed for time-series forecasting include:
* Recurrent Neural Networks (RNNs), especially LSTMs and GRUs:These architectures are designed to handle sequential data and capture temporal dependencies.
* Transformer Networks:Originally developed for NLP, Transformers have shown remarkable success in time-series forecasting due to their ability to capture long-range dependencies.
* Traditional statistical models:ARIMA, Exponential Smoothing, and other statistical methods remain powerful and interpretable options for time-series analysis.
Therefore, while "foundational models" have some potential, it's important to understand that they aren't the primary or specifically designed AI type for time-series forecasting.

質問 # 64
A data analyst must combine service calls into low-, medium-, and high-priority levels in order to analyze organizational responses. Which of the following techniques should the analyst use for this task?

• A. Augmentation
• B. Scaling
• C. Imputation
• D. Binning

正解：D

解説：
This question pertains to theData Analysisdomain, focusing on techniques for categorizing data. The task involves grouping service calls into priority levels (low, medium, high), which requires segmenting numerical or ordinal data into discrete categories.
* Augmentation (Option A): Augmentation involves adding data (e.g., in machine learning), not categorizing existing data.
* Imputation (Option B): Imputation fills in missing values, not relevant for categorizing priority levels.
* Scaling (Option C): Scaling adjusts numerical data to a common range (e.g., normalization), not suitable for creating priority categories.
* Binning (Option D): Binning groups continuous or ordinal data into discrete categories (e.g., assigning calls to low, medium, or high priority based on a metric like response time), which fits the task.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and binning is a standard technique for categorizing data for analysis.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

質問 # 65
A data analyst creates a report, and some of the fields are empty. Which of the following conditions should the analyst add to a query to provide a list of all the records with empty fields?

• A. WHERE [ColumnName] = NULL
• B. WHERE [ColumnName] = 'NULL'
• C. WHERE [ColumnName] IS NULL
• D. WHERE [ColumnName] IS NOT NULL

正解：C

解説：
This question falls under theData Analysisdomain, focusing on SQL queries to identify data issues. The task is to find records with empty fields, which in SQL means NULL values.
* WHERE [ColumnName] = NULL (Option A): In SQL, NULL cannot be compared using "="; this syntax is incorrect.
* WHERE [ColumnName] IS NULL (Option B): This is the correct SQL syntax to identify NULL values, which represent empty fields.
* WHERE [ColumnName] IS NOT NULL (Option C): This finds non-empty fields, the opposite of the requirement.
* WHERE [ColumnName] = 'NULL' (Option D): This checks for the string "NULL," not a true NULL value, which is incorrect.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," such as identifying NULL values with IS NULL.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

質問 # 66
A table contains several rows of cellular numbers with call timestamps, call durations, called numbers, and carriers of the called number. Which of the following allows a data analyst to sort the cellular numbers based on the carriers of the called numbers and include the total call durations?

• A. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrier;
• B. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number ORDER BY called_number_carrier;
• C. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number, called_number_carrier ORDER BY called_number_carrier;
• D. SELECT cellular_number, SUM(call_duration) FROM calls GROUP BY call_duration ORDERBY called_number_carrier;

正解：C

解説：
This question falls under theData Analysisdomain of CompTIA Data+ DA0-002, focusing on SQL queries for data analysis. The task requires sorting cellular numbers by the carrier of the called number (called_number_carrier) and calculating the total call durations (SUM(call_duration)).
* Option A: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number ORDER BY called_number_carrierThis query groups by cellular_number only, but called_number_carrier is in the SELECT clause without being in the GROUP BY, which is invalid in SQL (it would raise an error in most databases).
* Option B: SELECT cellular_number, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrierThis query doesn't include called_number_carrier in the SELECT clause, so it cannot be used in the ORDER BY clause, making it invalid. Grouping by call_duration also doesn't align with the task.
* Option C: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number, called_number_carrier ORDER BY called_number_carrierThis query correctly groups by both cellular_number and called_number_carrier (since both are in the SELECT clause), calculates the total call duration with SUM(call_duration), and sorts by called_number_carrier as required.
* Option D: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrierGrouping by call_duration is incorrect because cellular_number and called_number_carrier are in the SELECT clause but not in the GROUP BY, making this query invalid.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and Option C correctly aggregates and sorts the data as specified.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

質問 # 67
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?

• A. Filter the data in the dashboard.
• B. Confirm the dashboard is pointed to the newest dataset.
• C. Verify that the dashboard subscription is not expired.
• D. Escalate user permissions on the server.

正解：B

解説：
This question falls under theData Governancedomain, focusing on troubleshooting data freshness issues in dashboards. The dashboard shows stale data despite a successful refresh, and the server migration updated naming conventions, suggesting a potential mismatch.
* Confirm the dashboard is pointed to the newest dataset (Option A): The server migration updated dataset naming conventions, so the dashboard might still be pointing to an old dataset name, causing stale data. Confirming the dataset connection is the first step.
* Filter the data in the dashboard (Option B): Filtering might adjust the view but doesn't address the root cause of stale data.
* Escalate user permissions on the server (Option C): Permissions issues would likely prevent access, not cause stale data, especially since the dataset refreshed successfully.
* Verify that the dashboard subscription is not expired (Option D): An expired subscription might prevent access, but the dashboard is accessible, just showing stale data.
The DA0-002 Data Governance domain includes "data quality control concepts," such as ensuring dashboards connect to the correct, updated datasets after changes like server migrations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

質問 # 68
Which of the following best explains the purpose of data lineage?

• A. To look up data definitions, ensuring consistent use across business units
• B. To see the steps and path of data flow through different systems
• C. To better understand the granularity of data variable relationships
• D. To track data transformations from acquisition through reporting

正解：D

解説：
This question pertains to theData Concepts and Environmentsdomain, focusing on the purpose of data lineage. Data lineage involves tracking the lifecycle of data.
* To see the steps and path of data flow through different systems (Option A): This describes a data flow diagram, not data lineage, which focuses on transformations rather than just flow.
* To better understand the granularity of data variable relationships (Option B): This relates to data modeling, not the purpose of data lineage.
* To track data transformations from acquisition through reporting (Option C): Data lineage tracks the journey of data, including transformations (e.g., cleaning, aggregation) from its source to its final use in reporting, which is its primary purpose.
* To look up data definitions, ensuring consistent use across business units (Option D): This describes a data dictionary, not data lineage.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and data lineage specifically tracks transformations across the data lifecycle.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

質問 # 69
Which of the following best represents a type of infrastructure that requires a company to purchase and maintain all of its own servers?

• A. Hybrid
• B. Public
• C. Private
• D. Cloud

正解：C

解説：
This question pertains to theData Concepts and Environmentsdomain, focusing on types of server infrastructure. The task is to identify an infrastructure where a company owns and maintainsall servers.
* Private (Option A): A private infrastructure (often on-premises) means the company owns and maintains its own servers, typically in a private data center, which matches the requirement.
* Cloud (Option B): Cloud infrastructure is managed by third-party providers, not owned by the company.
* Hybrid (Option C): Hybrid combines on-premises and cloud, so not all servers are owned by the company.
* Public (Option D): Public infrastructure is a cloud model shared across multiple organizations, not owned by the company.
The DA0-002 Data Concepts and Environments domain includes understanding "data environments," and a private infrastructure requires the company to purchase and maintain its own servers.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

質問 # 70
A product goes viral on social media, creating high demand. Distribution channels are facing supply chain issues because the testing and training models that are used for sales forecasting have not encountered similar demand. Which of the following best describes this situation?

• A. Incorrect sizing
• B. Skewing
• C. Model bias
• D. Data drift

正解：D

解説：
This question pertains to theData Analysisdomain, focusing on issues with forecasting models. The scenario describes a sudden change in demand (viral product) that the model couldn't predict because it hasn't seen similar patterns before.
* Model bias (Option A): Model bias occurs when a model systematically favors certain outcomes due to flawed training data, but this scenario is about a change in data patterns, not bias.
* Data drift (Option B): Data drift occurs when the statistical properties of the data change over time (e.
g., sudden high demand due to virality), causing the model to perform poorly because it was trained on different patterns, which fits the scenario.
* Incorrect sizing (Option C): This term is vague and not a standard concept in data analysis for this context.
* Skewing (Option D): Skewing refers to data distribution asymmetry, not a change in data patterns affecting model performance.
The DA0-002 Data Analysis domain includes understanding "applying the appropriate descriptive statistical methods," and data drift is a key concept in forecasting when data patterns change unexpectedly.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

質問 # 71
A data analyst is following up on a recent, company-wide data audit of customer invoice data. Which of the following is the best option for the analyst to use?

• A. GDPR
• B. PCI DSS
• C. PII
• D. ISO

正解：A

解説：
This question falls under theData Governancedomain of CompTIA Data+ DA0-002, which includes understanding compliance frameworks for data audits, especially for customer data. The scenario involves a data audit of customer invoice data, which likely contains personal information, making privacy regulations relevant.
* PCI DSS (Option A): PCI DSS (Payment Card Industry Data Security Standard) applies specifically to payment card data, not general customer invoice data unless credit card details are involved, which isn't specified.
* GDPR (Option B): GDPR (General Data Protection Regulation) is a comprehensive privacy regulation for handling personal data of EU citizens, including customer invoice data, which may contain PII like names and addresses. It's the most relevant for a company-wide data audit.
* ISO (Option C): ISO standards (e.g., ISO 27001) relate to information security management but are not specific to customer data privacy audits.
* PII (Option D): PII (Personally Identifiable Information) is a concept, not a framework or tool for conducting an audit.
The DA0-002 Data Governance domain emphasizes "identifying PII and data privacy concepts," and GDPR is the most appropriate framework for auditing customer data to ensure compliance with privacy laws.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

質問 # 72
A data analyst is evaluating all conditions in a query. Which of the following is the best logical function to accomplish this task?

• A. OR
• B. AND
• C. IF
• D. NOT

正解：B

解説：
This question falls under theData Analysisdomain, focusing on SQL logical functions for query evaluation.
The task is to evaluate "all conditions," implying multiple conditions must be true together.
* OR (Option A): OR returns true if any condition is true, not ensuring all conditions are met.
* NOT (Option B): NOT negates a condition, not suitable for combining multiple conditions.
* AND (Option C): AND requires all conditions to be true, which aligns with evaluating "allconditions" in a query.
* IF (Option D): IF is a conditional function for decision-making, not for evaluating multiple conditions together.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and AND is the best logical function for ensuring all conditions are met.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

質問 # 73
Which of the following is found in metadata?

• A. Transformations
• B. Variable types
• C. Syntax
• D. Data lineage

正解：B

解説：
This question pertains to the Data Concepts and Environments domain, focusing on the content of metadata. Metadata describes data attributes, and the task is to identify what it typically includes.
* Transformations (Option A): Transformations (e.g., data cleaning steps) are part of data lineage, not metadata.
* Data lineage (Option B): Data lineage tracks data flow and transformations, which is related to metadata but not a direct component.
* Syntax (Option C): Syntax refers to code structure, not a metadata component.
* Variable types (Option D): Metadata includes information about data fields, such as variable types (e.
g., integer, string), which is a standard component.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and metadata typically contains details like variable types to describe the dataset.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

質問 # 74
A user needs a report that shows the main causes of customer churn rate in a three-year period. Which of the following methods provides this information?

• A. Predictive
• B. Descriptive
• C. Inferential
• D. Prescriptive

正解：B

解説：
This question falls under theData Analysisdomain, focusing on analytical methods for reporting. The task is to identify the causes of customer churn over three years, which involves analyzing historical data.
* Inferential (Option A): Inferential statistics make predictions or generalizations about a population, not focused on identifying causes in historical data.
* Descriptive (Option B): Descriptive analytics summarizes historical data to identify patterns and causes (e.g., reasons for churn), which fits the task.
* Prescriptive (Option C): Prescriptive analytics provides recommendations, which goes beyond identifying causes.
* Predictive (Option D): Predictive analytics forecasts future outcomes, not focused on historical causes.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and descriptive analytics is best for identifying causes in historical data.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

質問 # 75
A manager wants a report that contains the days off for each direct report. The manager needs this report to always be up-to-date with the latest data. Which of the following describes the refresh frequency that the manager is requesting?

• A. Real-time
• B. Snapshot
• C. Ad hoc
• D. Dynamic

正解：A

解説：
This question pertains to theVisualization and Reportingdomain, focusing on report refresh frequencies. The manager needs the report to always be up-to-date, implying continuous data updates.
* Real-time (Option A): Real-time refresh frequency ensures the report reflects the latest data as soon as it changes, which matches the requirement to "always be up-to-date."
* Ad hoc (Option B): Ad hoc reports are generated on-demand, not continuously updated.
* Snapshot (Option C): A snapshot captures data at a specific point in time, not suitable for always being up-to-date.
* Dynamic (Option D): Dynamic reports allow interactivity, but the term doesn't specifically imply real- time updates.
The DA0-002 Visualization and Reporting domain includes "the appropriate visualization in the form of a report" with delivery methods, and real-time refresh frequency ensures the report is always current.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.

質問 # 76
A data analyst deployed a report for public access. A user states that the report is not showing the latest information, even though the user updated the source an hour ago. Which of the following should the data analyst check first?

• A. Event log
• B. Report corruption
• C. Database connection
• D. User privileges

正解：C

解説：
This question pertains to theData Governancedomain, focusing on troubleshooting data freshness issues in reports. The report isn't showing the latest data despite a recent source update, indicating a potential refresh or connectivity issue.
* Event log (Option A): Event logs might provide insight into errors, but they're not the first step for checking data freshness.
* User privileges (Option B): Privileges might affect access, but the user can see the report, so this isn't the issue.
* Database connection (Option C): If the database connection failed or isn't refreshing properly, the report won't reflect the latest data, making this the first thing to check.
* Report corruption (Option D): Corruption might cause errors, but it's less likely than a connectivity issue for this scenario.
The DA0-002 Data Governance domain includes "data quality control concepts," such as ensuring data freshness by verifying database connections.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

質問 # 77
Given the following tables:
Individual table
ID
FirstName
LastName
1
John
Doe
Output
ID
FullName
1
JohnDoe
Which of the following is the best option to display output from FirstName and LastName as FullName?

• A. Group
• B. Concatenate
• C. Filter
• D. Join

正解：B

解説：
This question falls under theData Acquisition and Preparationdomain of CompTIA Data+ DA0-002, focusing on data manipulation techniques. The task is to combine FirstName and LastName into a single FullName field (e.g., "JohnDoe").
* Concatenate (Option A): Concatenation combines two or more strings into one (e.g., usingCONCAT in SQL or "+" in Python), which is the correct method to create FullName from FirstName and LastName.
* Filter (Option B): Filtering selects specific rows based on conditions, not suitable for combining fields.
* Join (Option C): Joining combines data from multiple tables, but the task involves manipulating data within a single table.
* Group (Option D): Grouping (e.g., GROUP BY in SQL) is for aggregation, not for combining fields into a new column.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and concatenation is the standard technique for combining fields like FirstName and LastName into FullName.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.

質問 # 78
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検証済みで更新されたDA0-002問題集と解答で100%一発合格保証の問題集：https://drive.google.com/open?id=112KHQxyjm1EkLhCxoQVsC_Nq_vur0YJg

更新されたDA0-002試験練習テスト問題：https://www.passtest.jp/CompTIA/DA0-002-shiken.html