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CompTIA Data+ Exam (2025) Sample Questions (Q103-Q108):
NEW QUESTION # 103
Which of the following data sources makes online data consumption easier?
- A. Web scraping
- B. Data mart
- C. Application programming interface
- D. Database
Answer: C
Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on data sources that facilitate online data access. The task is to identify a source that simplifies online data consumption.
* Data mart (Option A): A data mart stores structured data for specific business areas, typically accessed internally, not designed for online consumption.
* Web scraping (Option B): Web scraping extracts data from websites but requires parsing and cleaning, which isn't necessarily "easier."
* Database (Option C): Databases store data but aren't inherently designed for online consumption without an interface.
* Application programming interface (Option D): An API provides a structured way to access data online, often in formats like JSON, making data consumption easier for applications and users.
The DA0-002 Data Concepts and Environments domain includes understanding "data sources," and APIs are specifically designed to simplify online data access.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
NEW QUESTION # 104
A recent server migration applied an update to dataset naming conventions. Multiple users are now reporting stale information in an existing dashboard. The date in the dataset confirms a successful data refresh. Which of the following should a data analyst do first?
- A. Confirm the dashboard is pointed to the newest dataset.
- B. Verify that the dashboard subscription is not expired.
- C. Escalate user permissions on the server.
- D. Filter the data in the dashboard.
Answer: A
Explanation:
This question falls under theData Governancedomain, focusing on troubleshooting data freshness issues in dashboards. The dashboard shows stale data despite a successful refresh, and the server migration updated naming conventions, suggesting a potential mismatch.
* Confirm the dashboard is pointed to the newest dataset (Option A): The server migration updated dataset naming conventions, so the dashboard might still be pointing to an old dataset name, causing stale data. Confirming the dataset connection is the first step.
* Filter the data in the dashboard (Option B): Filtering might adjust the view but doesn't address the root cause of stale data.
* Escalate user permissions on the server (Option C): Permissions issues would likely prevent access, not cause stale data, especially since the dataset refreshed successfully.
* Verify that the dashboard subscription is not expired (Option D): An expired subscription might prevent access, but the dashboard is accessible, just showing stale data.
The DA0-002 Data Governance domain includes "data quality control concepts," such as ensuring dashboards connect to the correct, updated datasets after changes like server migrations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
NEW QUESTION # 105
A data company needs a visualization that shows the availability zones from the last ten years and any future availability zones that the company will be using in the next five years. Which of thefollowing is the most appropriate visualization to display this information?
- A. Mosaic plot
- B. Pie chart
- C. Bar chart
- D. Map
Answer: D
Explanation:
This question falls under theVisualization and Reportingdomain of CompTIA Data+ DA0-002, focusing on selecting the appropriate visualization for a specific dataset. The task is to show availability zones over a 15- year period (past and future), which involves a geographical element since availability zones are typically location-based.
* Bar chart (Option A): Bar charts are good for comparing categorical data but don't effectively show geographical locations or time-based trends across zones.
* Mosaic plot (Option B): Mosaic plots display relationships between categorical variables, not suitable for geographical or time-series data.
* Map (Option C): A map can display availability zones geographically, with annotations or layers to show changes over time (past 10 years and future 5 years), making it the most appropriate visualization.
* Pie chart (Option D): Pie charts show proportions of a whole, not suitable for geographical or time- based data.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a map is the best choice for displaying geographical availability zones over time.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.
NEW QUESTION # 106
The director of operations at a power company needs data to help identify where company resources should be allocated in order to monitor activity for outages and restoration of power in the entire state. Specifically, the director wants to see the following:
* County outages
* Status
* Overall trend of outages
INSTRUCTIONS:
Please, select each visualization to fit the appropriate space on the dashboard and choose an appropriate color scheme. Once you have selected all visualizations, please, select the appropriate titles and labels, if applicable.
Titles and labels may be used more than once.
If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.
Answer:
Explanation:
Power outages
Explanation:
This is a simulation question that requires you to create a dashboard with visualizations that meet the director' s needs.Here are the steps to complete the task:
* Drag and drop the visualization that shows the county outages on the top left space of the dashboard.
This visualization is a map of the state with different colors indicating the number of outages in each county. You can choose any color scheme that suits your preference, but make sure that the colors are consistent and clear. For example, you can use a gradient of red to show the counties with more outages and green to show the counties with less outages.
* Drag and drop the visualization that shows the status of the outages on the top right space of the dashboard. This visualization is a pie chart that shows the percentage of outages that are active, restored, or pending. You can choose any color scheme that suits your preference, but make sure that the colors are distinct and easy to identify. For example, you can use red for active, green for restored, and yellow for pending.
* Drag and drop the visualization that shows the overall trend of outages on the bottom space of the dashboard. This visualization is a line graph that shows the number of outages over time. You can choose any color scheme that suits your preference, but make sure that the color is visible and contrasted with the background. For example, you can use blue for the line and white for the background.
* Select appropriate titles and labels for each visualization. Titles and labels may be used more than once.
For example, you can use "County Outages" as the title for the map, "Status" as the title for the pie chart, and "Trend" as the title for the line graph. You can also use "County", "Number of Outages",
"Active", "Restored", "Pending", "Time", and "Number of Outages" as labels for the axes and legends of the visualizations.
NEW QUESTION # 107
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?
- A. Boolean data and an array
- B. Numerical and ordinal attributes
- C. Standard deviation and constraints
- D. Mean and median
Answer: B
Explanation:
This question pertains to theData Analysisdomain, focusing on data types and methods for forecasting. The task involves projecting sales (numerical) and customer satisfaction (likely ordinal,e.g., ratings), requiring appropriate data attributes.
* Standard deviation and constraints (Option A): Standard deviation measures data spread, and constraints are conditions, neither of which directly supports forecasting.
* Mean and median (Option B): Mean and median are descriptive statistics, not sufficient for forecasting future values.
* Boolean data and an array (Option C): Boolean data (true/false) and arrays (data structures) are not relevant for forecasting sales and satisfaction.
* Numerical and ordinal attributes (Option D): Sales are numerical (e.g., units sold), and customer satisfaction is often ordinal (e.g., 1-5 ratings). These attributes are suitable for forecasting models (e.g., time-series analysis for sales, regression for satisfaction).
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and numerical and ordinal attributes are key for forecasting sales and satisfaction.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 108
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