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CompTIA DA0-002 Exam Overview:

Certification Vendor:CompTIA
Exam Name:CompTIA Data+ Exam
Exam Number:DA0-002
Exam Price:$255 USD
Exam Duration:90 minutes
Exam Format:Performance-based questions, Multiple-choice
Real Exam Qty:Up to 90
Certificate Validity Period:3 years
Available Languages:English
Passing Score:720 (scale 100โ€“900)
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 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
  • 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
  • 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 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
  • 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 (Q142-Q147):

NEW QUESTION # 142
A data analyst must create a report to analyze the flow of services from call receipt to service completion using established time points. Which of the following techniques should the analyst use to create the needed variables?

Answer: C

Explanation:
Calculating is used to create new variables from existing data through mathematical operations.
To analyze the flow of services between call receipt and service completion using established time points, the analyst would calculate variables such as elapsed time, service duration, or response time from the existing timestamps.


NEW QUESTION # 143
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: B

Explanation:
This question pertains to theData Analysisdomain, focusing on techniques for categorizing data. The task involves grouping service calls into priority levels (low, medium, high), which requires segmenting numerical or ordinal data into discrete categories.
* Augmentation (Option A): Augmentation involves adding data (e.g., in machine learning), not categorizing existing data.
* Imputation (Option B): Imputation fills in missing values, not relevant for categorizing priority levels.
* Scaling (Option C): Scaling adjusts numerical data to a common range (e.g., normalization), not suitable for creating priority categories.
* Binning (Option D): Binning groups continuous or ordinal data into discrete categories (e.g., assigning calls to low, medium, or high priority based on a metric like response time), which fits the task.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and binning is a standard technique for categorizing data for analysis.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 144
The human resources department wants to understand the relationship between the ages and incomes of all employees. Which of the following graphics is the most appropriate to present the analysis?

Answer: B

Explanation:
This question pertains to theVisualization and Reportingdomain, focusing on selecting the appropriate visualization to show a relationship between two continuous variables (ages and incomes).
* Scatter plot (Option A): A scatter plot displays individual data points on two axes (age vs. income), making it ideal for showing the relationship and potential correlation between two continuous variables.
* Area plot (Option B): Area plots are used for showing trends over time, not relationships between two variables.
* Bar chart (Option C): Bar charts are better for categorical data comparisons, not continuous variable relationships.
* Pie chart (Option D): Pie charts show proportions of a whole, not suitable for showing relationships between variables.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a scatter plot is best for showing the relationship between age and income.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.


NEW QUESTION # 145
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: D

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 # 146
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 # 147
......

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