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CompTIA DA0-002 Exam Overview:

Certification Vendor:CompTIA
Exam Name:CompTIA Data+ Certification Exam
Exam Number:DA0-002
Available Languages:English
Real Exam Qty:Up to 90
Passing Score:675 (on a scale of 100–900)
Exam Duration:90 minutes
Exam Price:$253 USD (may vary by region/tax)
Certificate Validity Period:3 years
Exam Format:Performance-based questions, Multiple-choice, Multiple-response
Recommended Training:CompTIA CertMaster Learn for Data+
CompTIA Data+ Study Resources
Exam Registration:CompTIA Data+ Certification Page
Pearson VUE CompTIA Exams Registration
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 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
  • 5.0 Data Governance, Quality, and Controls
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.

CompTIA Data+ Exam Sample Questions (Q74-Q79):

NEW QUESTION # 74
Which of the following file types separates data using a delimiter?

Answer: C

Explanation:
This question falls under theData Concepts and Environmentsdomain, focusing on understanding file formats and their structures. The task is to identify a file type that uses delimiters to separate data.
* XML (Option A): XML uses tags to structure data, not delimiters.
* HTML (Option B): HTML is a markup language for web pages, not a data file format using delimiters.
* JSON (Option C): JSON uses key-value pairs and nested structures, not delimiters like commas.
* CSV (Option D): CSV (Comma-Separated Values) uses delimiters (typically commas) to separate data fields, making it the correct choice.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," such as file formats like CSV that use delimiters.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 75
A company has a document that includes the names of key metrics and the standard for how those metrics are calculated company-wide. Which of the following describes this documentation?

Answer: C


NEW QUESTION # 76
A sales manager wants a dashboard that shows sales aggregated by region and identifies high-volume sales by salesperson per region. Which of the following communication techniques best displays this information?

Answer: B

Explanation:
This question pertains to theVisualization and Reportingdomain, focusing on dashboard features for displaying data. The dashboard needs to show aggregated sales by region and allow identification of high- volume sales by salesperson within each region.
* Defined parameters (Option A): Parameters set specific values (e.g., a date range), but they don't directly enable interaction with aggregated data.
* Filter options (Option B): Filter options allow the user to select a region and then view salespersons within that region, enabling the identification of high-volume sales per region interactively.
* Level of detail (Option C): Level of detail determines the granularity of data shown but doesn't facilitate interactive exploration.
* User persona (Option D): User personas guide dashboard design but aren't a communication technique for displaying data.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and filter options best enable the interactive analysis required.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.


NEW QUESTION # 77
Which of the following data repositories stores unaltered data?

Answer: A

Explanation:
This question falls under theData Concepts and Environmentsdomain, focusing on data repositories. The task is to identify a repository that stores data in its original, unaltered form.
* Data lake (Option A): A data lake stores raw, unaltered data in its native format (structured, semi- structured, or unstructured), making it the correct choice.
* Data warehouse (Option B): A data warehouse stores processed, structured data, often transformed for analysis, not unaltered.
* Data table (Option C): A data table is a structure within a database, not a repository, and may contain altered data.
* Data factory (Option D): A data factory (e.g., Azure Data Factory) is a data integration service, not a repository for storing data.
The DA0-002 Data Concepts and Environments domain includes understanding "different types of databases and data repositories," and a data lake is designed to store unaltered data.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 78
A data analyst is creating a new dataset that involves bringing together the following datasets:

Which of the following would be the output if the data analyst does a FULL JOIN?

Answer: A

Explanation:
A FULL JOIN returns all records from both tables. Matching records are combined based on the common ID field, while nonmatching records from either table are still included with null or blank values for the missing columns.
In the source data:
ID 23525 exists in both tables, so Frank is combined with the Chicago address.
ID 11290 exists in both tables, so Martha is combined with the Miami address.
ID 12141 exists only in the first table, so Ellen appears with blank address information.
ID 11040 exists only in the second table, so the address record appears with blank name and date-of-birth information.


NEW QUESTION # 79
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