DA0-002 — CompTIA Data+ (V2)
CompTIA

CompTIA Data+ (V2) (DA0-002) Practice Questions

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100 questions
June 14, 2026 updated
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Domain coverage

  • Data Concepts and Environments (17%)
  • Data Acquisition and Preparation (23%)
  • Data Analysis (30%)
  • Visualization and Reporting (20%)
  • Data Governance (10%)

Sample Questions (10 of 100 shown)

Q1 Data Concepts and Environments (20%)
A company has a document containing names of key metrics and the standard calculation criteria for these metrics across the company. Which term describes this document?
  1. Data dictionary
  2. Data explainability report
  3. Data lineage
  4. Data flow diagram
✓ Correct Answer: A
A data dictionary defines business terms, metrics, data types, and calculation logic. It provides a reference for analysts to understand what each metric means and how it is computed, ensuring consistency across teams.
Q2 Data Concepts and Environments (20%)
Which of the following best describes the approach used to combine files, software, and libraries for use across various operating systems and environments?
  1. Containerization
  2. Code repository
  3. Package manager
  4. Virtual machine
✓ Correct Answer: A
Containerization packages an application together with its dependencies (libraries, binaries, configuration files) into a single container image that runs consistently across different environments. Containers are lightweight compared to virtual machines.
Q3 Data Concepts and Environments (20%)
A data analyst profiles API records before loading them into a relational reporting table. The record shows nested fields such as customer containing address and items as an array. Which interpretation is best supported?
  1. The record is unstructured because it has no fixed columns
  2. The record contains hierarchical and repeated nested fields
  3. The record has duplicate orders that should be removed
  4. The record is a flat delimited file with embedded separators
✓ Correct Answer: B
Semi-structured data such as JSON can include fields inside other fields (hierarchical) and arrays of repeated values (nested). The exhibit shows customer with child fields and items as an array, meaning a relational load may need parsing and flattening.
Q4 Data Concepts and Environments (20%)
A data analyst is reviewing how a weekly sales packet is created. The tool run log shows: sign in to sales portal, click Export CSV, open KPI workbook, refresh workbook data, export PDF report, email PDF to managers. Which concept is best illustrated?
  1. Data lakehouse ingestion
  2. Robotic process automation
  3. Natural language processing
  4. Manual ad hoc analysis
✓ Correct Answer: B
Robotic process automation (RPA) uses software to perform repetitive, rule-based steps that a person would otherwise do. The sequence of signing in, clicking export, refreshing, and emailing represents an automated workflow mimicking user actions.
Q5 Data Concepts and Environments (20%)
A team is deploying a relational database that will support an internal reporting application. The storage requirements include frequent random reads/writes, mounting by one database server, and need for low-level volume, partition, and file system control. Which storage type best fits?
  1. File storage
  2. Object storage
  3. Block storage
  4. Data lake storage
✓ Correct Answer: C
Block storage is the best fit when a database needs low-level volume-style storage behavior. It presents storage as attachable volumes that the server can format with a file system and use for random read/write workloads, matching database requirements.
Q6 Data Concepts and Environments (20%)
A product team wants to analyze why mobile checkout sessions fail after a new release. An analyst reviews timestamped source data showing session_id, component, event, and status values such as WARN and ERROR. Which interpretation is best supported?
  1. It is log data for event and error analysis
  2. It is a transaction ledger for revenue reporting
  3. It is reference data for product categorization
  4. It is survey data for customer sentiment analysis
✓ Correct Answer: A
Log data records what systems and applications do over time. The exhibit contains timestamped events tied to a session and component, with status values like WARN and ERROR, supporting analysis of failure sequences and event patterns.
Q7 Data Concepts and Environments (20%)
A retail analytics team maintains a star schema for sales reporting. The business wants quarterly sales to remain tied to the customer segment that was active when each sale occurred, even if a customer's segment changes later. Which dimension-table approach best supports this?
  1. Overwrite the segment in the customer dimension
  2. Use a Type 2 slowly changing dimension
  3. Store only the previous segment in a new column
  4. Remove customer segment from the sales model
✓ Correct Answer: B
A Type 2 slowly changing dimension (SCD) preserves historical attribute values by adding a new dimension row for each changed version with effective dates. This allows facts to remain associated with the correct historical dimension version.
Q8 Data Concepts and Environments (20%)
A retail analyst is comparing AI tools for automated reporting. Tool A is pretrained on large text corpora and generates SQL explanations and summaries. Tool B is pretrained on text, image, and audio, adaptable for captioning, transcription, and document search. Which interpretation is correct?
  1. Both tools are only LLMs because both can process text
  2. Tool A is a foundation model; Tool B is only RPA
  3. Tool A is an LLM; Tool B is a broader foundation model
  4. Neither tool uses AI unless trained from scratch internally
✓ Correct Answer: C
An LLM focuses on language tasks like generating and summarizing text. A foundation model is the broader category pretrained on large datasets adaptable to many tasks. Tool A is language-centered (LLM), while Tool B supports multiple data types (broader foundation model).
Q9 Data Concepts and Environments (20%)
Which of the following is used to store and manage structured data using tables with rows and columns, supporting SQL queries?
  1. Non-relational database
  2. Relational database
  3. File storage
  4. Object storage
✓ Correct Answer: B
A relational database organizes data into tables with rows and columns, enforces schema constraints, and supports Structured Query Language (SQL) for data manipulation and retrieval.
Q10 Data Concepts and Environments (20%)
A retail analytics team needs one repository for raw clickstream logs, product images, and curated sales tables. Data scientists need raw files for experimentation, while BI users need governed SQL reporting with documented lineage. Which repository concept best fits?
  1. Flat file repository
  2. Operational database
  3. Data lakehouse
  4. Data silo
✓ Correct Answer: C
A data lakehouse combines the flexibility of a data lake for raw diverse data with the managed analytics features of a data warehouse for curated tables and SQL reporting, making it ideal for this mixed workload.

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Exam overview

The CompTIA Data+ (DA0-002) is the latest version of CompTIA's entry-level data analytics certification, designed for professionals working with data in business environments. Released in 2025 as V2, this exam validates your ability to transform raw data into actionable business intelligence across the full data lifecycle—from data acquisition and preparation to analysis, visualization, and governance. Unlike vendor-specific data certifications, Data+ is vendor-neutral and focuses on universal data concepts, tools, and methodologies that apply across platforms.

Our DA0-002 practice test platform offers 500+ original practice questions aligned to the latest V2 exam objectives. Each question includes detailed explanations, scenario-based contexts, and exam tips to help you master the material. The practice tests cover all 5 domains with weighted accuracy, ensuring you can collect data from appropriate sources, perform analysis using statistical methods, create effective visualizations, and implement data governance best practices. With our PBQ simulator, you'll practice designing dashboards, performing data cleaning operations, conducting statistical analysis, and implementing data privacy controls—exactly what you'll face on exam day.

Whether you're a business analyst seeking to validate your data skills, a report specialist creating data-driven insights, or an IT professional bridging the gap between technical and business teams, our practice tests adapt to your role. The intelligent feedback system tracks your progress across all domains, identifies knowledge gaps, and generates targeted study plans. Combined with our scenario-based practice questions, you can study real-world data problems anytime, anywhere. Join thousands of data professionals who've earned their Data+ certification with our proven practice test system. Start your free trial today and transform your data analytics career.

Official Exam Domains & Weighting

To successfully pass the DA0-002 exam, candidates must master data analytics skills across the following five core domains:
  • Domain 1: Data Concepts and Environments (17%) – Understand data types, structures, storage concepts, and data lifecycle stages.
  • Domain 2: Data Acquisition and Preparation (23%) – Collect data from appropriate sources, perform data cleaning, transformation, and validation using ETL processes.
  • Domain 3: Data Analysis (30%) – Apply descriptive, predictive, and inferential statistical methods, identify data trends and patterns, and perform data mining.
  • Domain 4: Visualization and Reporting (20%) – Create effective visualizations, design dashboards and reports, and communicate insights to stakeholders.
  • Domain 5: Data Governance (10%) – Implement data quality standards, ensure data privacy and compliance, and manage data security throughout the lifecycle.

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Frequently Asked Questions

Data+ is vendor-neutral and covers the full data lifecycle using universal concepts and tools. Unlike platform-specific certifications (Tableau, Power BI, Google Analytics), Data+ validates foundational data skills that apply across all data platforms and tools.

Most candidates study for 4-8 weeks, depending on their data analysis experience. CompTIA recommends some familiarity with data concepts, but there are no formal prerequisites.

Yes! Our PBQ simulator mirrors the real exam experience. You'll practice designing dashboards, performing data cleaning operations, conducting statistical analysis, and implementing data governance controls in a simulated environment.

You need a scaled score of 720 on a scale of 100-900. Our practice tests use the same scoring algorithm, so you'll know exactly when you're ready.

The exam covers vendor-neutral data concepts and may reference common tools like Excel, SQL, Python (pandas), Tableau, and Power BI. However, the focus is on concepts and methodologies, not specific tool proficiency.

Data+ prepares you for roles like Business Analyst, Data Technician, Reporting Specialist, Junior Data Analyst, and Marketing/Operations Analyst. It's ideal for professionals who work with data but don't have "data analyst" in their job title.

Yes! The V2 update (DA0-002) includes expanded coverage of AI concepts, machine learning basics, and their application in data analytics workflows.