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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
  • 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 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.

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CompTIA Data+ Exam Sample Questions (Q164-Q169):

NEW QUESTION # 164
Which of the following best describes an assessment a data analyst would use to validate that the number of records in a dataset matches the expected results?

Answer: A

Explanation:
This question pertains to theData Governancedomain, focusing on data quality validation techniques. The task is to validate that the number of records matches expectations, which requires a specific type of assessment.
* Source control (Option A): Source control (e.g., Git) manages code versions, not dataset validation.
* Unit test (Option B): A unit test checks a specific component of a process, such as verifying that the number of records in a dataset matches the expected count, making it the best fit.
* Stress test (Option C): Stress tests evaluate system performance under load, not record counts.
* Health check (Option D): A health check monitors system status but isn't specific to validating record counts.
The DA0-002 Data Governance domain includes "data quality control concepts," and unit tests are a standard method for validating specific data outcomes like record counts.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.


NEW QUESTION # 165
Which of the following data repositories stores unformatted data in its original, raw form?

Answer: B


NEW QUESTION # 166
A data analyst pulls a table similar to the following one:
ID
Type
TypeID
Phone
1
Full Time
Full Time 1
Mobile
2
Part Time
Part Time 2
Work
3
Full Time
Full Time 3
Mobile
Which of the following best explains the data issue with TypeID?

Answer: D

Explanation:
This question is part of theData Concepts and Environmentsdomain, focusing on identifying data quality issues. The table shows Type and TypeID columns, where TypeID seems to repeat information from Type with an additional identifier.
* Redundancy (Option A): The TypeID column (e.g., "Full Time 1") redundantly includes the Type value ("Full Time") with an extra identifier, which is unnecessary and could be simplified by using a numeric ID instead.
* Outlier (Option B): Outliers are data points that deviate significantly, which isn't applicable here.
* Missing data (Option C): There are no missing values in the table.
* Duplication (Option D): Duplication refers to identical rows, but the rows here are unique; the issue is with the column content.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and redundancy is a common data quality issue in schema design.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 167
A data breach occurs at a company. Which of the following actions should be taken?

Answer: A

Explanation:
A data breach must be reported internally to management and then to appropriate regulatory authorities to ensure proper incident response, legal compliance, and coordinated communication.


NEW QUESTION # 168
A data analyst is building a new report on sales data. The analyst wants to find the total sales per channel, but only for those channels which have a total sales higher than 20.0. Given the following:

Which of the following should the analyst use?

Answer: D

Explanation:
To find the total sales per channel, the query must aggregate sales values using SUM(VALUE) and group the results by channel. Because the requirement is to return only channels whose total sales exceed 20.0, the aggregate result must be filtered with a HAVING clause. HAVING SUM(VALUE) > 20.0 correctly filters the grouped totals after aggregation.


NEW QUESTION # 169
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