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CompTIA DA0-002 Exam Overview:

Certification Vendor:CompTIA
Exam Name:CompTIA Data+ Exam
Exam Number:DA0-002
Real Exam Qty:Up to 90
Exam Format:Multiple-choice, Performance-based questions
Certificate Validity Period:3 years
Exam Price:$255 USD
Available Languages:English
Passing Score:720 (scale 100โ€“900)
Exam Duration:90 minutes
Recommended Training:CompTIA Official Training
Exam Registration:CompTIA Official Registration
Pearson VUE Testing
Sample Questions:CompTIA DA0-002 Sample Questions
Exam Way:Online proctored or onsite at Pearson VUE test centers
Pre Condition:Recommended 18โ€“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
  • 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 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
  • 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 4
  • 5.0 Data Governance, Quality, and Controls
Topic 5
  • 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 (Q16-Q21):

NEW QUESTION # 16
Which of the following is the best reason for a company to use a CSV file to share data instead of an Excel file?

Answer: C

Explanation:
CSV files are not tied to a specific software vendor and can be opened, imported, and processed by a wide variety of applications and platforms. This makes CSV an ideal format for sharing data between different systems and organizations.


NEW QUESTION # 17
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


NEW QUESTION # 18
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 # 19
A data analyst is creating a forecast for a product line introduced early last year. Which of the following should the analyst use to create projected sales and customer satisfaction for next year?

Answer: A

Explanation:
Numerical attributes are used for quantitative forecasting such as projected sales, while ordinal attributes represent ordered categories like customer satisfaction levels, making them appropriate for forecasting both types of outcomes.


NEW QUESTION # 20
A data analyst needs to create a report that anticipates the number of calls received daily. Which of the following is the best statistical method to use?

Answer: C

Explanation:
This question falls under theData Analysisdomain, focusing on statistical methods for forecasting. The task is to anticipate (predict) the number of daily calls, which involves looking into the future.
* Predictive (Option A): Predictive analytics uses historical data to forecast future outcomes (e.g., number of calls), which matches the requirement.
* Diagnostic (Option B): Diagnostic analytics identifies causes and patterns in historical data, not future predictions.
* Inferential (Option C): Inferential statistics make generalizations about a population, not specific forecasts.
* Descriptive (Option D): Descriptive analytics summarizes past data, not suitable for anticipating future values.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and predictive analytics is the best method for forecasting future call volumes.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 21
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