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CompTIA Data+ Exam (2025) Sample Questions (Q108-Q113):
NEW QUESTION # 108
A sales manager wants to understand how sales are trending year over year. Which of the following chart types is the most appropriate to display the information?
- A. Bubble
- B. Donut
- C. Hierarchy
- D. Line
Answer: D
Explanation:
This question falls under theVisualization and Reportingdomain, focusing on selecting the appropriate visualization for a specific data trend. The task is to show sales trends over time (year over year).
* Line (Option A): Line charts are ideal for displaying trends over time, such as year-over-year sales, as they clearly show changes and patterns across a continuous time axis.
* Donut (Option B): Donut charts show proportions or percentages of a whole, not suitable for time- based trends.
* Bubble (Option C): Bubble charts display three dimensions of data (e.g., size, x-axis, y-axis), not ideal for simple time trends.
* Hierarchy (Option D): Hierarchy charts (e.g., treemaps) show nested relationships, not time-based trends.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a line chart is best for time-series trends.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.
NEW QUESTION # 109
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. An error in SQL code
- D. Lack of permissions
Answer: C
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* Report refresh failure (Option C): A refresh failure would result in outdated data, not specifically current-month data.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 # 110
A data analyst needs to join together a table data source and a web API data source using Python. Which of the following is the best way to accomplish this task?
- A. Convert the data from the API and database to a TXT format and convert them to pandas DataFrames that are then merged together.
- B. Convert the data from the API and database to a JSON format and convert them to pandas DataFrames that are then merged together.
- C. Convert the data from the API and database to a string format and convert them to pandas DataFrames that are then merged together.
- D. Convert the data from the API and database to a varchar format and convert them to pandas DataFrames that are then merged together.
Answer: B
Explanation:
This question falls under theData Acquisition and Preparationdomain of CompTIA Data+ DA0-002, which involves acquiring and combining data from different sources, such as a database and a web API, using tools like Python. The task requires joining the data, which in Python often involves using pandas DataFrames.
* Convert the data from the API and database to a varchar format and convert them to pandas DataFrames that are then merged together (Option A): VARCHAR is a databasedata type for strings, not a format for data exchange or merging in Python, making this incorrect.
* Convert the data from the API and database to a JSON format and convert them to pandas DataFrames that are then merged together (Option B): Web APIs commonly return data in JSON format, and databases can export data as JSON. In Python, JSON data can be easily converted to pandas DataFrames using pandas.read_json() or pandas.DataFrame(), and then merged using pandas.merge() on a common key, making this the best approach.
* Convert the data from the API and database to a TXT format and convert them to pandas DataFrames that are then merged together (Option C): TXT is a generic text format that lacks structure, making it less efficient for merging compared to JSON.
* Convert the data from the API and database to a string format and convert them to pandas DataFrames that are then merged together (Option D): Converting to a string format is vague and not a standard approach for structured data merging in Python.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as combining data from APIs and databases, and JSON is a standard format for this purpose in Python.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.
NEW QUESTION # 111
A data analyst needs to create and deliver a dashboard that displays the company's financial transactions as they are updated. Which of the following delivery methods should the analyst consider? (Select two).
- A. Ad hoc
- B. Dynamic
- C. Real-time
- D. Snapshot
- E. Time series
- F. Static
Answer: B,C
Explanation:
This question is part of theVisualization and Reportingdomain, focusing on delivery methods for dashboards. The requirement for displaying financial transactions "as they are updated" implies a need for real-time updates and interactivity, which narrows down the options.
* Real-time (Option A): Real-time delivery ensures the dashboard reflects the latest data as transactions are updated, meeting the requirement.
* Snapshot (Option B): A snapshot provides a static view at a specific point, not suitable for ongoing updates.
* Dynamic (Option C): A dynamic dashboard allows for interactivity and can be updated as data changes, complementing real-time delivery.
* Static (Option D): Static dashboards don't update automatically, making this incorrect.
* Ad hoc (Option E): Ad hoc delivery is for one-time reports, not ongoing updates.
* Time series (Option F): Time series refers to a data type or visualization, not a delivery method.
The DA0-002 Visualization and Reporting domain includes understanding "the appropriate visualization in the form of a report or dashboard" with delivery methods Real-time and dynamic methods best support the need for updated financial transaction dashboards.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization andReporting
NEW QUESTION # 112
Which of the following best describes the semi-structured data that is gathered when web scraping?
- A. CSV
- B. CSS
- C. JSON
- D. HTML
Answer: C
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 # 113
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