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CompTIA DA0-002 Exam Overview:

Certification Vendor:CompTIA
Exam Name:CompTIA Data+ Exam
Exam Number:DA0-002
Exam Duration:90 minutes
Real Exam Qty:Up to 90
Certificate Validity Period:3 years
Exam Price:$255 USD
Exam Format:Multiple-choice, Performance-based questions
Passing Score:720 (scale 100–900)
Available Languages:English
Recommended Training:CompTIA Official Training
Exam Registration:Pearson VUE Testing
CompTIA Official Registration
Sample Questions:CompTIA DA0-002 Sample Questions
Exam Way:Online proctored or onsite at Pearson VUE test centers
Pre Condition:Recommended 18–24 months of experience in data/business analysis role; familiarity with databases, analytical tools, basic statistics, and visualization
Official Syllabus URL:https://www.comptia.org/certifications/data

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CompTIA DA0-002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • This section of the exam measures skills of a Data Governance Associate and introduces principles for keeping data secure, accurate, and compliant. It covers access controls, encryption, classification of sensitive data like PII and PHI, and legal requirements tied to data use. Candidates must know how to apply quality checks, validate data, and manage master data effectively. It also addresses best practices for maintaining integrity through data dictionaries, audits, and standardisation processes.
Topic 2
  • Data Analysis: This section of the exam measures skills of a Reporting Analyst and includes foundational knowledge of statistical methods such as averages, variances, and standard deviation. It covers how to use data to find patterns, track performance, and make predictions. This domain also introduces hypothesis testing, regression, correlation, and different types of analysis like exploratory and trend analysis. Candidates should also be aware of common tools used for analysis, including Excel, SQL, Python, R, and popular BI platforms like Tableau and Power BI.
Topic 3
  • Data Mining: This section of the exam measures skills of a Business Intelligence Analyst and covers how data is collected, cleaned, and prepared for analysis. It explains methods like ETL and ELT for data integration, as well as web scraping, API use, and survey data collection. Candidates are expected to identify issues like missing or duplicated data and apply techniques like filtering, sorting, merging, and normalizing. The section also touches on query optimization strategies to improve data handling efficiency.
Topic 4
  • Data Concepts and Environments: This section of the exam measures the skills of a Junior Data Analyst and focuses on understanding core data concepts such as database types, schema structures, and data formats. It highlights differences between structured and unstructured data, compares file types like CSV, JSON, and XML, and introduces key ideas about data dimensions and slowly changing dimensions. Knowing how data is stored and organized helps professionals better prepare for analysis and reporting tasks.
Topic 5
  • Visualization: This section of the exam measures skills of a Data Visualisation Specialist and focuses on turning raw data into clear, visual insights. It teaches how to match visual formats like bar charts, heat maps, and line graphs to specific audiences and needs. Candidates must understand how to create dashboards and reports using proper design elements such as labels, layout, branding, and colour schemes. This section also includes best practices for dashboard development and delivery through various platforms and user access levels.

CompTIA Data+ Exam Sample Questions (Q37-Q42):

NEW QUESTION # 37
Which of the following is a NoSQL database?

Answer: A


NEW QUESTION # 38
Given the following table:
ID
Value
1
1.5
2
24.456
3
113
Which of the following data types should an analyst use for the numeric values in the Value column?

Answer: D

Explanation:
This question falls under theData Concepts and Environmentsdomain of CompTIA Data+ DA0-002, focusing on selecting appropriate data types for a given dataset. The Value column contains decimal numbers (1.5, 24.456, 113), requiring a data type that supports such values.
* Double (Option A): Double is a floating-point data type that supports decimals with higher precision than Float, but it's often overkill for typical datasets unless very high precision is needed, which isn't indicated here.
* Float (Option B): Float is a floating-point data type that supports decimal numbers (e.g., 1.5, 24.456) and is commonly used for such values in databases, making it the best choice.
* Boolean (Option C): Boolean is for true/false values, not numeric data.
* Integer (Option D): Integer is for whole numbers, but the values (e.g., 1.5, 24.456) have decimals, so Integer is not suitable.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," such as selecting data types like Float for decimal numeric values.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 39
Which of the following tables holds relational keys and numeric values?

Answer: D


NEW QUESTION # 40
Which of the following tables holds relational keys and numeric values?

Answer: D

Explanation:
This question falls under theData Concepts and Environmentsdomain, focusing on understanding table types in data warehousing. The task is to identify a table that holds relational keys and numeric values, typically used in a star schema.
* Fact (Option A): Fact tables in a star schema store quantitative data (numeric values, e.g., sales amounts) and foreign keys (relational keys) linking to dimension tables, making this the correct choice.
* Graph (Option B): Graph tables are used in graph databases for relationships (e.g., nodes, edges), not typically for relational keys and numeric values in a traditional sense.
* Dimensional (Option C): Dimension tables store descriptive attributes (e.g., product names) and primary keys, not typically numeric measures.
* Transactional (Option D): Transactional tables are used in OLTP systems and may contain numeric values, but they're not specifically designed for relational keys in a data warehousing context.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and fact tables are designed to hold relational keys and numeric values in a data warehouse.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 41
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?

Answer: A


NEW QUESTION # 42
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