매달, 우리는 1000명 이상의 사람들이 시험 준비를 잘하고 시험을 잘 통과할 수 있도록 도와줍니다.
CompTIA Data+ Exam (2025) 온라인 연습
최종 업데이트 시간: 2026년06월04일
당신은 온라인 연습 문제를 통해 CompTIA DA0-002 시험지식에 대해 자신이 어떻게 알고 있는지 파악한 후 시험 참가 신청 여부를 결정할 수 있다.
시험을 100% 합격하고 시험 준비 시간을 35% 절약하기를 바라며 DA0-002 덤프 (최신 실제 시험 문제)를 사용 선택하여 현재 최신 121개의 시험 문제와 답을 포함하십시오.
정답:
Explanation:
This question pertains to the Data Concepts and Environments domain, focusing on tools for interacting with relational databases. The task is to identify the best method for retrieving and manipulating data.
XML (Option A): XML is a data format, not a language for retrieving or manipulating database data.
SQL (Option B): SQL (Structured Query Language) is specifically designed for querying and manipulating data in relational databases (e.g., SELECT, UPDATE), making it the best choice.
Excel (Option C): Excel can analyze data but isn’t designed for direct database manipulation.
JavaScript (Option D): JavaScript is a programming language for web development, not optimized for relational database operations.
The DA0-002 Data Concepts and Environments domain includes understanding "different types of databases," and SQL is the standard language for relational database operations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
정답:
Explanation:
This question falls under the Data Governance domain, focusing on optimizing data quality and performance in dashboards. The dashboard is slow because it pulls from a large database (30 years) but only needs seven years of data.
Performing a code review (Option A): A code review might identify inefficiencies, but it’s not the most direct solution for this scenario.
Checking network connectivity (Option B): Network issues might cause delays, but the primary issue is the data volume, not connectivity.
Filtering to include only relevant data (Option C): Filtering the data to include only the last seven years reduces the dataset size, directly improving performance by minimizing the data processed.
Adding more RAM and rerunning (Option D): Adding RAM might help, but it’s a hardware solution that doesn’t address the root cause of excessive data.
The DA0-002 Data Governance domain includes "data quality control concepts," such as optimizing performance by filtering data to improve efficiency.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
정답:
Explanation:
This question pertains to the Visualization and Reporting domain, focusing on selecting the appropriate visualization for a specific requirement. The task is to show the composition of total sales across three channels, which involves showing proportions.
Pivot table (Option A): A pivot table summarizes data but isn’t a visualization; it’s more for data exploration.
Pie chart (Option B): A pie chart shows the proportion of total sales for each channel (Digital, Store, Online), which is ideal for displaying composition.
KPI card (Option C): A KPI card displays a single metric, not suitable for showing composition across multiple channels.
Box plot (Option D): A box plot shows data distribution (e.g., quartiles), not proportions.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a pie chart is best for showing the composition of totals.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.
정답:
Explanation:
This question falls under the Data Analysis domain, 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.
정답:
Explanation:
This question pertains to the Data Concepts and Environments domain, focusing on data sources that facilitate online data access. The task is to identify a source that simplifies online data consumption.
Data mart (Option A): A data mart stores structured data for specific business areas, typically accessed internally, not designed for online consumption.
Web scraping (Option B): Web scraping extracts data from websites but requires parsing and cleaning, which isn’t necessarily "easier."
Database (Option C): Databases store data but aren’t inherently designed for online consumption without an interface.
Application programming interface (Option D): An API provides a structured way to access data online, often in formats like JSON, making data consumption easier for applications and users.
The DA0-002 Data Concepts and Environments domain includes understanding "data sources," and APIs are specifically designed to simplify online data access.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
정답:
Explanation:
This question falls under the Data Analysis domain, focusing on selecting the appropriate function type to filter data in a query. The task is to flag customers who made a purchase in January, which involves a conditional check.
Statistical (Option A): Statistical functions (e.g., AVG, STDEV) analyze data distributions, not suitable
for flagging specific months.
Logical (Option B): Logical functions (e.g., WHERE Month = 'January' in SQL) are used to apply conditions and flag rows based on criteria, which fits the task.
Mathematical (Option C): Mathematical functions (e.g., SUM, ROUND) perform calculations, not conditional flagging.
Date (Option D): Date functions (e.g., MONTH()) manipulate dates, but the Month column is already in text format, so a logical comparison is sufficient.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and logical functions are best for conditional flagging.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
정답:
Explanation:
This question pertains to the Data Governance domain, 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.
정답:
Explanation:
This question falls under the Visualization and Reporting domain, focusing on selecting the appropriate visualization for a specific data trend. The task is to show sales trends over time (year over year).
Line (Option A): Line charts are ideal for displaying trends over time, such as year-over-year sales, as they clearly show changes and patterns across a continuous time axis.
Donut (Option B): Donut charts show proportions or percentages of a whole, not suitable for time-based trends.
Bubble (Option C): Bubble charts display three dimensions of data (e.g., size, x-axis, y-axis), not ideal for simple time trends.
Hierarchy (Option D): Hierarchy charts (e.g., treemaps) show nested relationships, not time-based trends.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a line chart is best for time-series trends.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.
정답:
Explanation:
This question pertains to the Data Analysis domain, focusing on statistical measures. The middle 50% of a dataset refers to a specific statistical concept related to data distribution.
Interquartile range (Option A): The interquartile range (IQR) is the range between the first quartile (Q1, 25th percentile) and the third quartile (Q3, 75th percentile), representing the middle 50% of the data, which matches the description.
The difference between mode and median (Option B): This measures the spread between two central tendency metrics but doesn’t represent the middle 50% of the data.
Mean variance (Option C): Variance measures data dispersion around the mean, not the middle 50%.
Skewness from the slope (Option D): Skewness measures data asymmetry, and "slope" is irrelevant here.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and the IQR is the standard measure for the middle 50% of a dataset.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
정답:
Explanation:
This question falls under the Data Acquisition and Preparation domain of CompTIA Data+ DA0-002, which involves acquiring and combining data from different sources, such as a database and a web API, using tools like Python. The task requires joining the data, which in Python often involves using pandas DataFrames.
Convert the data from the API and database to a varchar format and convert them to pandas DataFrames that are then merged together (Option A): VARCHAR is a database data type for strings, not a format for data exchange or merging in Python, making this incorrect.
Convert the data from the API and database to a JSON format and convert them to pandas DataFrames that are then merged together (Option B): Web APIs commonly return data in JSON format, and databases can export data as JSON. In Python, JSON data can be easily converted to pandas DataFrames using pandas.read_json() or pandas.DataFrame(), and then merged using pandas.merge() on a common key, making this the best approach.
Convert the data from the API and database to a TXT format and convert them to pandas DataFrames that are then merged together (Option C): TXT is a generic text format that lacks structure, making it less efficient for merging compared to JSON.
Convert the data from the API and database to a string format and convert them to pandas DataFrames that are then merged together (Option D): Converting to a string format is vague and not a standard approach for structured data merging in Python.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as combining data from APIs and databases, and JSON is a standard format for this purpose in Python.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.
정답:
Explanation:
This question pertains to the Data Governance domain, focusing on ensuring data quality and reliability in dashboards over time. Daily troubleshooting indicates a recurring issue, and the task is to validate data moving forward.
Inquiring about structure changes (Option A): This might identify past issues but doesn’t provide ongoing validation.
Setting up monitoring alerts (Option B): Monitoring alerts can automatically notify the analyst of data issues (e.g., missing updates, errors), providing a proactive way to validate data continuously.
Reaching out to users daily (Option C): This is inefficient and reactive, not a sustainable validation method.
Rebuilding the dashboard (Option D): Rebuilding might fix current issues but doesn’t ensure future validation.
The DA0-002 Data Governance domain includes "data quality control concepts," such as implementing monitoring to ensure data reliability in dashboards.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
정답:
Explanation:
This question falls under the Data Analysis domain, 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 "all conditions" 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.
정답:
Explanation:
This question pertains to the Data Concepts and Environments domain, focusing on selecting the appropriate repository for structured data across an entire company. The requirement for a predefined structure narrows the options.
Data mart (Option A): A data mart stores structured data for a specific business area (e.g., sales), not the whole company.
Data warehouse (Option B): A data warehouse is designed to store structured data from across the entire company in a predefined schema, optimized for analytics and reporting.
Data silo (Option C): A data silo is an isolated repository, often structured, but not designed for company-wide integration.
Data lake (Option D): A data lake stores raw data (structured and unstructured) without a predefined structure, not suitable for this requirement.
The DA0-002 Data Concepts and Environments domain includes understanding "different types of databases and data repositories," and a data warehouse is ideal for company-wide structured data.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
정답:
Explanation:
This question falls under the Data Governance domain, focusing on data breach response protocols.
A data breach requires a structured response to comply with legal and regulatory requirements.
Make an announcement on social media so customers are aware as soon as possible (Option A): Public announcement without internal coordination or regulatory notification can lead to legal issues and loss of trust.
Tell the company management team and then tell regulatory agencies (Option B): This follows best practices: inform internal leadership to coordinate a response, then notify regulatory agencies as required by laws (e.g., GDPR mandates notification within 72 hours).
Keep the incident a secret until the issue is resolved (Option C): This violates regulations requiring timely breach notification.
Inform the entire IT sector, but ask for discretion (Option D): Sharing with the IT sector is vague and risks leaks; regulatory agencies should be prioritized.
The DA0-002 Data Governance domain includes "data privacy concepts," such as proper breach response procedures, emphasizing internal and regulatory notification.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
정답:
Explanation:
This question pertains to the Visualization and Reporting domain, focusing on report delivery methods. The requirement for delivery every seven days indicates a scheduled, repeating process.
Recurring (Option A): Recurring delivery schedules reports to be generated and delivered at regular intervals (e.g., weekly), which matches the requirement of every seven days.
Ad hoc (Option B): Ad hoc reports are one-time, on-demand reports, not suitable for scheduled delivery.
Custom (Option C): Custom isn’t a standard delivery method; it might refer to tailored reports but doesn’t imply scheduling.
Snapshot (Option D): A snapshot captures data at a specific point, not suitable for recurring delivery.
The DA0-002 Visualization and Reporting domain includes "the appropriate visualization in the form of a report" with delivery methods, and recurring delivery is ideal for weekly reports.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.