CompTIA Data+ DA0-002 Practice Test & Mock Exam

Start with the free diagnostic or public sample questions. IT Mastery gives you a stable, exam-domain-mapped practice bank with timed mocks, topic drills, progress tracking, and detailed explanations across web and mobile.

Initial release: this CompTIA Data+ DA0-002 bank currently includes 759 questions. We expand high-demand banks first based on learner usage, feedback, and subscriber demand. Subscribers receive access to future additions automatically.

Free diagnostic: Try the 90-question CompTIA Data+ DA0-002 full-length practice exam before subscribing.

CompTIA Data+ V2 (DA0-002) is CompTIA’s current early-career data analytics route for candidates who need practical judgment around data concepts, acquisition, preparation, analysis, visualization, reporting, governance, and quality.

DA0-002 is the newer Data+ V2 lane, so current preparation should include data quality, governance, reporting, and AI-adjacent analytics context rather than older data-literacy material alone. This page includes original sample questions, exam guidance, and live IT Mastery practice.

Who DA0-002 is for

• early-career data analysts and reporting professionals who need a vendor-neutral analytics credential
• candidates learning how to gather, clean, analyze, visualize, and govern data
• learners comparing Data+ with Databricks, Snowflake, Oracle SQL, or cloud data-engineering routes

DA0-002 exam snapshot

• Vendor: CompTIA
• Official exam name: CompTIA Data+ V2
• Exam code: DA0-002
• Launch date shown by CompTIA: October 14, 2025
• Question count shown by CompTIA: maximum of 90, including multiple-choice and performance-based questions
• Exam time shown by CompTIA: 90 minutes
• Passing score shown by CompTIA: 675 on a 100-900 scale
• Recommended experience shown by CompTIA: 18-24 months in a data analyst or similar job role

Data+ questions usually reward the option that improves data reliability, chooses the right analysis or visual for the audience, and preserves governance controls instead of jumping straight to a tool-specific shortcut.

Topic coverage for DA0-002

Focused sample questions

Use these child pages when you want focused IT Mastery practice before returning to mixed sets and timed mocks.

• Free CompTIA Data+ DA0-002 Full-Length Practice Exam
• Data Concepts and Environments
• Data Acquisition and Preparation
• Data Analysis
• Visualization and Reporting
• Data Governance

Free study resources

Need concept review first? Read the CompTIA Data+ DA0-002 Cheat Sheet on Tech Exam Lexicon, then return to IT Mastery for timed practice.

Sample Exam Questions

Try these 12 original sample questions for CompTIA Data+ V2 DA0-002. Use them for study, self-assessment, and exam-scope review.

Question 1

What this tests: data type selection

A data analyst imports a customer table. The ZIP code column contains values such as 02139 and should not be used in mathematical calculations. Which data type is most appropriate?

• A. Text or string
• B. Integer
• C. Floating-point number
• D. Boolean

Best answer: A

Explanation: ZIP codes are identifiers, not quantities. Treating them as numbers can remove leading zeros and invite invalid calculations. Data+ questions often test whether the analyst understands the meaning of a field before choosing a type.

Question 2

What this tests: join choice

An analyst needs a report showing every active customer, including customers who have not placed an order yet. Customer details are in one table and orders are in another. Which join is the best fit if the customer table is on the left?

• A. Inner join
• B. Left join
• C. Cross join
• D. Self join

Best answer: B

Explanation: A left join keeps all rows from the left table and matches order rows where they exist. An inner join would exclude customers without orders. A cross join creates combinations, and a self join compares rows within the same table.

Question 3

What this tests: missing data handling

A survey field is missing for 35% of responses, and the missingness appears related to respondent age. What should the analyst do first?

• A. Replace every missing value with zero
• B. Delete the column without documenting the decision
• C. Assume the missing responses are random and continue
• D. Investigate the missing-data pattern and document the chosen treatment

Best answer: D

Explanation: Missingness that relates to another variable can bias results. The analyst should evaluate the pattern, choose an appropriate treatment, and document the limitation. Blind deletion or blanket replacement can distort the analysis.

Question 4

What this tests: visualization fit

An executive wants to compare monthly revenue trends across the last 18 months. Which visualization is usually the clearest first choice?

• A. Pie chart with 18 slices
• B. Word cloud
• C. Box plot by customer segment
• D. Line chart with months on the x-axis

Best answer: D

Explanation: A line chart is well suited to showing change over time. Pie charts are poor for many time periods, word clouds are not quantitative trend visuals, and box plots summarize distributions rather than a single time series.

Question 5

What this tests: data quality dimensions

A product table has duplicate product IDs, invalid category names, and prices stored in multiple currencies without a currency field. Which issue is the analyst primarily facing?

• A. Data encryption failure
• B. Data quality problems that affect uniqueness, validity, and consistency
• C. A visualization color-palette issue only
• D. A normal form that requires no cleanup

Best answer: B

Explanation: Duplicate IDs, invalid categories, and inconsistent currency context are data quality problems. They can affect joins, calculations, and interpretation. Data+ expects candidates to recognize quality dimensions before analysis.

Question 6

What this tests: outlier response

A sales dataset contains one transaction that is 100 times larger than all others. The analyst is preparing a report for average order size. What is the best next step?

• A. Delete the transaction automatically
• B. Ignore it because averages are never affected by outliers
• C. Validate whether the transaction is real, then decide whether to report the mean with context or use a more robust measure
• D. Convert every amount to text

Best answer: C

Explanation: Outliers can be valid or erroneous. The analyst should validate the record and then choose a suitable summary, such as reporting the median or explaining the effect on the mean. Automatic deletion is not defensible.

Question 7

What this tests: correlation interpretation

A dashboard shows a strong positive correlation between two variables. What is the safest interpretation?

• A. One variable definitely causes the other
• B. The variables move together, but causation is not proven by correlation alone
• C. The data must be invalid
• D. The variables are unrelated

Best answer: B

Explanation: Correlation describes an association. It does not prove causation without study design, controls, and supporting evidence. This is a common analytics reasoning trap.

Question 8

What this tests: aggregation grain

A dataset contains one row per order item. An analyst wants average order value. What should the analyst do before calculating the average?

• A. Average every item price directly
• B. Count the number of columns in the table
• C. Aggregate item rows to the order level, then average order totals
• D. Sort item names alphabetically

Best answer: C

Explanation: Average order value requires order-level totals. Averaging item rows would answer a different question: average item value. Data+ scenarios often test whether the analyst matches calculation grain to the business question.

Question 9

What this tests: governance and access control

A marketing analyst asks for raw customer data that includes sensitive personal information, but the report only needs age bands and region. What should the data team provide?

• A. Full raw records because the analyst asked for them
• B. Public access to the database
• C. A spreadsheet with passwords removed but all other sensitive fields intact
• D. Only the minimum required fields or aggregated data needed for the report

Best answer: D

Explanation: Data governance favors minimum necessary access. If age bands and region satisfy the analysis, raw personal data should not be exposed. This reduces privacy and compliance risk while still supporting the business need.

Question 10

What this tests: metric definition

Two departments report different churn rates because one uses canceled accounts and the other uses inactive accounts. What is the best analyst response?

• A. Define the metric, numerator, denominator, time window, and inclusion rules before comparing results
• B. Average the two churn rates and publish the result
• C. Use whichever number is lower
• D. Delete both reports

Best answer: A

Explanation: Metric disagreements often come from different definitions. A clear definition of numerator, denominator, period, and filters is required before comparing or reconciling results.

Question 11

What this tests: dashboard audience fit

A dashboard for executives should summarize sales performance and highlight exceptions. Which design choice best supports that audience?

• A. Raw transaction table with thousands of rows as the first view
• B. A dense chart for every available metric
• C. High-level KPIs, trend visuals, and drill-down paths for details
• D. Hidden filters with no labels

Best answer: C

Explanation: Executive dashboards usually need concise KPIs, trends, and exception cues, with drill-downs available when needed. Raw row dumps and overcrowded visuals make decisions harder.

Question 12

What this tests: sampling bias

A company surveys only customers who recently left a five-star review, then uses the results to represent all customers. What is the main concern?

• A. The sample may be biased and not representative of the customer population
• B. The survey has too many rows for analysis
• C. Five-star reviewers are always statistically identical to all customers
• D. The data must be encrypted before any chart can be created

Best answer: A

Explanation: Sampling only highly satisfied reviewers can bias results and overstate satisfaction. Data+ expects candidates to recognize sampling limitations and explain how they affect conclusions.

Data+ analysis workflow map

    flowchart LR
	    A["Business question"] --> B["Acquire data"]
	    B --> C["Clean and validate"]
	    C --> D["Analyze and compare"]
	    D --> E["Visualize findings"]
	    E --> F["Report limits, risks, and next action"]
	    C --> G["Protect privacy and governance"]
	    G --> F

Use the map when a Data+ item asks what to do next. Strong answers preserve the business question, check data quality before analysis, and communicate limits instead of overclaiming what the data proves.

Quick Cheat Sheet

Mini Glossary

• Data lineage: The record of where data came from, how it changed, and where it was used.
• Cardinality: The relationship count between tables or fields, such as one-to-one or one-to-many.
• KPI: A key performance indicator tied to a business objective.
• Outlier: A value far from the expected pattern that may be valid, erroneous, or worth separate investigation.
• Normalization: Structuring data to reduce duplication or scaling values to make comparisons more meaningful, depending on context.

CompTIA Data+ V2 DA0-002 practice update

Use this page to review DA0-002 sample questions and use the Notify me form for exam updates. The related pages below help you compare adjacent IT Mastery data practice options before choosing what to study next.

Use these live IT Mastery pages now

Practice options

• Current status: Sample questions available
• Full practice bank: Not available yet
• Best use right now: confirm the DA0-002 analytics lane here, then practise with SQL, Databricks, Snowflake, or AWS data pages before the full Data+ bank is available
• Update form: use the Notify me form near the top of this page if Data+ V2 is your actual target exam

Official sources

• CompTIA Data+ V2
• CompTIA Data+ overview

What to open next

• Need SQL practice now? Open Oracle Database SQL 1Z0-071 .
• Need data-engineering practice now? Open Databricks Data Engineer Associate .
• Need the CompTIA hub? Open CompTIA .

In this section

• CompTIA Data+ DA0-002: Data Concepts and Environments
  Try 10 focused CompTIA Data+ DA0-002 questions on Data Concepts and Environments, with explanations, then continue with IT Mastery.
• CompTIA Data+ DA0-002: Data Acquisition and Preparation
  Try 10 focused CompTIA Data+ DA0-002 questions on Data Acquisition and Preparation, with explanations, then continue with IT Mastery.
• CompTIA Data+ DA0-002: Data Analysis
  Try 10 focused CompTIA Data+ DA0-002 questions on Data Analysis, with explanations, then continue with IT Mastery.
• CompTIA Data+ DA0-002: Visualization and Reporting
  Try 10 focused CompTIA Data+ DA0-002 questions on Visualization and Reporting, with explanations, then continue with IT Mastery.
• CompTIA Data+ DA0-002: Data Governance
  Try 10 focused CompTIA Data+ DA0-002 questions on Data Governance, with explanations, then continue with IT Mastery.
• Free CompTIA Data+ DA0-002 Full-Length Practice Exam: 90 Questions
  Try 90 free CompTIA Data+ DA0-002 questions across the exam domains, with explanations, then continue with full IT Mastery practice.