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CompTIA Data+ Exam (2025) Sample Questions (Q10-Q15):
NEW QUESTION # 10
Which of the following best describes the semi-structured data that is gathered when web scraping?
- A. HTML
- B. CSS
- C. CSV
- D. JSON
Answer: D
Explanation:
This question pertains to theData Acquisition and Preparationdomain, which in DA0-002 includes understanding data acquisition concepts and the types of data gathered from varioussources, such as web scraping. Web scraping involves extracting data from websites, and the data gathered is often semi-structured, meaning it has some organizational structure but isn't fully relational like a database table.
* JSON (Option A): JSON (JavaScript Object Notation) is a semi-structured data format commonly used in web applications. Web scraping often retrieves data in JSON format via APIs or embedded scripts, as it's lightweight and structured with key-value pairs, making it ideal for semi-structured data.
* CSV (Option B): CSV (Comma-Separated Values) is a structured format typically used for tabular data. It's not commonly the direct output of web scraping, though scraped data might be converted to CSV later.
* CSS (Option C): CSS (Cascading Style Sheets) is used for styling web pages and isn't a data format, making it irrelevant for describing scraped data.
* HTML (Option D): HTML (HyperText Markup Language) is the structure of web pages and is often the raw format scraped during web scraping. While HTML is semi-structured due to its tag-based hierarchy, it's primarily a markup language, not a data format, and the actual data extracted is often parsed into formats like JSON.
The DA0-002 Data Acquisition and Preparation domain aligns with the DA0-001 focus on "data acquisition concepts" (web ID: 14), which includes identifying formats like JSON as semi-structured data commonly acquired through web scraping. JSON is the best fit here due to its prevalence in web data exchange.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation
NEW QUESTION # 11
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?
- A. Area plot
- B. Scatter plot
- C. Pie chart
- D. Bar chart
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 # 12
A data analyst learns that a report detailing employee sales is reflecting sales only for the current month.
Which of the following is the most likely cause?
- A. Report refresh failure
- B. Connectivity issues
- C. Lack of permissions
- D. An error in SQL code
Answer: D
Explanation:
This question falls under theData Analysisdomain, focusing on troubleshooting issues in data reports. The report should show all employee sales but is limited to the current month, suggesting a data retrieval issue.
* Lack of permissions (Option A): Permissions issues would likely prevent access entirely, not limit data to the current month.
* An error in SQL code (Option B): The report likely uses an SQL query to retrieve data, and an error (e.g., a WHERE clause filtering for the current month) could restrict the data to the current month, making this the most likely cause.
* Report refresh failure (Option C): A refresh failure would result in outdated data, not specifically current-month data.
* Connectivity issues (Option D): Connectivity issues would likely prevent the report fromrunning, not limit it to a specific time frame.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and errors in SQL code are a common cause of incorrect data retrieval in reports.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 13
A data analyst is joining two tables with different content and one common field. Which of the following should the analyst do to most efficiently meet this requirement?
- A. Append the values of the matching columns and concatenate the other data fields.
- B. Match the records of the related columns and merge the tables.
- C. Create a cluster to facilitate data integration between the tables.
- D. Explode both tables to identify unique values and reorder the fields in one table.
Answer: B
Explanation:
This question falls under theData Acquisition and Preparationdomain, focusing on combining data from multiple tables. The tables have different content but share a common field, indicating a join operation.
* Match the records of the related columns and merge the tables (Option A): This describes a join operation, where records are matched on the common field (e.g., a key like Customer_ID) and the tables are merged, which is the most efficient method.
* Create a cluster to facilitate data integration between the tables (Option B): Clustering is a machine learning technique, not a method for joining tables.
* Explode both tables to identify unique values and reorder the fields in one table (Option C):
Exploding is used in nested data (e.g., JSON arrays), and this approach is overly complex and unnecessary.
* Append the values of the matching columns and concatenate the other data fields (Option D):
Appending stacks tables vertically, and concatenation applies to text, neither of which is appropriate for joining tables with a common field.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as joining tables using a common field.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.
NEW QUESTION # 14
A data analyst wants to understand several datasets at the variable level. Which of the following should the analyst consult to find this information?
- A. Data versioning
- B. Data lineage
- C. Data dictionary
- D. Data flow diagram
Answer: C
Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on documentation for understanding datasets. The analyst needs variable-level details (e.g., field definitions), which points to a specific type of documentation.
* Data lineage (Option A): Data lineage tracks data flow and transformations, not variable definitions.
* Data dictionary (Option B): A data dictionary provides detailed information about variables (e.g., name, type, description), which is exactly what the analyst needs.
* Data flow diagram (Option C): A data flow diagram shows data movement, not variable-level details.
* Data versioning (Option D): Data versioning tracks changes to datasets, not variable definitions.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and a data dictionary is the primary tool for variable-level information.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
NEW QUESTION # 15
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