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CompTIA DA0-002 Exam Overview:

Certification Vendor:	CompTIA
Exam Name:	CompTIA Data+ Exam (2025)
Exam Number:	DA0-002
Certificate Validity Period:	3 years
Exam Price:	USD 255
Exam Format:	Multiple-choice, Performance-based
Available Languages:	English
Passing Score:	720 (scale of 100–900)
Real Exam Qty:	Up to 90
Exam Duration:	90 minutes
Related Certifications:	CompTIA Data+
Sample Questions:	CompTIA DA0-002 Sample Questions
Exam Way:	Online proctored or at Pearson VUE authorized testing centers
Pre Condition:	No formal prerequisites; recommended 18–24 months of experience in a report/business analyst role or equivalent knowledge
Official Syllabus URL:	https://www.comptia.org/certifications/data

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CompTIA DA0-002 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	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.
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.

CompTIA Data+ Exam Sample Questions (Q62-Q67):

NEW QUESTION # 62
A data analyst is creating a dashboard to monitor and manage processes on a daily, weekly, and quarterly basis. Which of the following types of dashboards is the best for this purpose?

A. Operational
B. Strategic
C. Tactical
D. Analytical

Answer: C

Explanation:
Tactical dashboards focus on monitoring and managing processes over medium-term periods like daily, weekly, and quarterly, supporting mid-level management decisions.

NEW QUESTION # 63
Which of the following is the most efficient to use when programming repeatable tasks?

A. RPA
B. NLP
C. LLM
D. Deep learning

Answer: A

Explanation:
Robotic process automation is designed to automate repetitive, rule-based tasks, making it the most efficient choice for repeatable processes.

NEW QUESTION # 64
Which of the following best describes the reason an analyst would reference a data dictionary versus a source's metadata?

A. To gather information about the availability of the data
B. To find the content and specific attributes for a dataset
C. To find a summary of basic information about the dataset
D. To gather information and resources about the data

Answer: B

Explanation:
A data dictionary provides detailed definitions of fields, including their meaning, structure, and attributes, which helps an analyst understand the specific contents of a data set.

NEW QUESTION # 65
A data analyst wants to use the following tables to find all the customers who have not placed an order:
Customers table
ID
Name
Address
Products table
ID
Name
Customer_ID
Which of the following SQL statements is the best way to accomplish this task?

A. SELECT * FROM PRODUCTS AS P LEFT JOIN CUSTOMERS AS C ON P.Customer_ID = C.ID WHERE P.Customer_ID IS NOT NULL
B. SELECT * FROM CUSTOMERS AS C LEFT JOIN PRODUCTS AS P ON C.ID = P.Customer_ID WHERE P.Customer_ID IS NULL
C. SELECT * FROM CUSTOMERS AS C INNER JOIN PRODUCTS AS P ON C.ID = C.IDWHERE COUNT(P.) = 0
D. SELECT * FROM PRODUCTS AS P INNER JOIN CUSTOMERS AS C ON P.Customer_ID = C.ID WHERE (SELECT COUNT(P.) = 0)

Answer: B

Explanation:
This question pertains to theData Analysisdomain, focusing on SQL queries to analyze data relationships.
The task is to find customers who have not placed an order, meaning customers in the Customers table without a matching Customer_ID in the Products table.
* Option A: SELECT * FROM CUSTOMERS AS C LEFT JOIN PRODUCTS AS P ON C.ID = P.
Customer_ID WHERE P.Customer_ID IS NULLA LEFT JOIN includes all customers, even those without orders (where Products columns are NULL). Filtering with WHERE P.Customer_ID IS NULL selects only customers without a match in Products, correctly identifying those who haven't ordered.
* Option B: SELECT * FROM CUSTOMERS AS C INNER JOIN PRODUCTS AS P ON C.ID = C.
ID WHERE COUNT(P.*) = 0An INNER JOIN only includes matching records, so it won't return customers without orders. The join condition C.ID = C.ID is also incorrect, and COUNT requires a GROUP BY, making this invalid.
* Option C: SELECT * FROM PRODUCTS AS P INNER JOIN CUSTOMERS AS C ON P.
Customer_ID = C.ID WHERE (SELECT COUNT(P.*) = 0)An INNER JOIN excludes customers without orders, and the subquery syntax is incorrect (COUNT needs a GROUP BY or to be part of a HAVING clause).
* Option D: SELECT * FROM PRODUCTS AS P LEFT JOIN CUSTOMERS AS C ON P.
Customer_ID = C.ID WHERE P.Customer_ID IS NOT NULLThis starts with Products and joins Customers, returning only records with orders (opposite of the task), and IS NOT NULL further excludes non-ordering customers.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and a LEFT JOIN with a NULL check is the standard method for finding non-matching records.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

NEW QUESTION # 66
A data analyst is cleaning up a data set that contains images. The analysts wants to keep everything that was produced within the last 12 months. Which of the following best describes where the analyst should check for the date of creation on these products?

A. The data set creation date on the database
B. The data dictionary of the data set
C. The metadata of each item in the data set
D. The folder creation date on the filesystem

Answer: C

Explanation:
Metadata contains descriptive information about each file or image, including attributes such as creation date, modification date, file size, and format. To determine which images were produced within the last 12 months, the analyst should examine the metadata of each item rather than the creation date of the dataset or folder containing the files.

NEW QUESTION # 67
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