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CompTIA DA0-002 Exam Overview:

Certification Vendor:CompTIA
Exam Name:CompTIA Data+ Certification Exam
Exam Number:DA0-002
Exam Duration:90 minutes
Exam Price:$253 USD (may vary by region/tax)
Available Languages:English
Certificate Validity Period:3 years
Real Exam Qty:Up to 90
Exam Format:Performance-based questions, Multiple-response, Multiple-choice
Passing Score:675 (on a scale of 100–900)
Recommended Training:CompTIA CertMaster Learn for Data+
CompTIA Data+ Study Resources
Exam Registration:Pearson VUE CompTIA Exams Registration
CompTIA Data+ Certification Page
Sample Questions:CompTIA DA0-002 Sample Questions
Exam Way:Delivered via Pearson VUE testing centers or online proctored exam
Pre Condition:No mandatory prerequisites. Recommended: 18–24 months of experience in a business/data analytics environment.
Official Syllabus URL:https://www.comptia.org/certifications/data-plus

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CompTIA DA0-002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 5.0 Data Governance, Quality, and Controls

CompTIA Data+ Exam Sample Questions (Q94-Q99):

NEW QUESTION # 94
A data analyst must combine service calls into low-, medium-, and high-priority levels in order to analyze organizational responses. Which of the following techniques should the analyst use for this task?

Answer: D

Explanation:
Binning groups values into defined categories, such as low, medium, and high priority levels, enabling structured analysis of service call responses.


NEW QUESTION # 95
A data analyst is preparing a report for external users. The analyst must ensure that visuals can be identified as belonging to the organization. Which of the following should the analyst add to the report to best meet this requirement?

Answer: A

Explanation:
A watermark embeds visible branding such as a logo or organization name into visuals, ensuring they are clearly identifiable as belonging to the organization.


NEW QUESTION # 96
A data analyst wants to find the mean score that students received in science classes. Given the following tables:

Which of the following will produce the desired results?

Answer: B

Explanation:
Filtering the data to include only science classes and then applying an average function on the corresponding scores calculates the mean score for those students.


NEW QUESTION # 97
A data analyst wants to isolate a serial number from a string of code. Which of the following data transformation techniques should the analyst use?

Answer: A

Explanation:
Parsing separates a string into its individual components based on a defined pattern or delimiter.
To isolate a serial number from a larger string of code, the analyst would use parsing to extract the specific portion containing the serial number.


NEW QUESTION # 98
A data analyst receives four files that need to be unified into a single spreadsheet for further analysis. All of the files have the same structure, number of columns, and field names, but each file contains different values.
Which of the following methods will help the analyst convert the files into a single spreadsheet?

Answer: C

Explanation:
This question is part of theData Acquisition and Preparationdomain, which involves combining data from multiple sources. The files have the same structure but different values, meaning theyneed to be stacked vertically into one dataset.
* Merging (Option A): Merging typically involves joining datasets on a common key (e.g., a customer ID), which isn't indicated here since the files only differ in values, not keys.
* Appending (Option B): Appending stacks datasets vertically, combining rows from files with the same structure into a single dataset, which matches the scenario.
* Parsing (Option C): Parsing involves breaking down data (e.g., splitting text), not combining files.
* Clustering (Option D): Clustering is a machine learning technique for grouping similar data points, not for combining files.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as appending datasets with identical structures.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.


NEW QUESTION # 99
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