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CompTIA Data+ Exam (2025) Sample Questions (Q72-Q77):

NEW QUESTION # 72
A data analyst needs to modify a dashboard that was created by another employee. Upon opening the dashboard, the analyst notices that the information is not loading properly. Which of the following should the analyst do to troubleshoot this error?

A. Check that the program is updated to the latest version.
B. Review the data layer and data source.
C. Validate that the database is up-to-date.
D. Ensure the correct filters are displaying on the dashboard.

Answer: B

Explanation:
This question falls under theData Governancedomain of CompTIA Data+ DA0-002, focusing on troubleshooting data quality issues in dashboards. The dashboard isn't loading properly, indicating a potential issue with the data connection or configuration.
* Review the data layer and data source (Option A): The data layer (e.g., queries, connections) and data source (e.g., database) are the foundation of a dashboard. If the information isn't loading, the issue likely lies in the data connection or query configuration, making this the first step.
* Validate that the database is up-to-date (Option B): While this might be a subsequent step, it assumes the connection is working, which should be confirmed first.
* Check that the program is updated to the latest version (Option C): Software updates might fix bugs, but this isn't the most immediate cause of data not loading.
* Ensure the correct filters are displaying on the dashboard (Option D): Filters affect data display, but if the data isn't loading at all, the issue is more fundamental.
The DA0-002 Data Governance domain includes "data quality control concepts," and reviewing the data layer and source is the primary step in troubleshooting dashboard loading issues.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 73
A data analyst created a dashboard to illustrate the traffic volume and mean response time for a call center.
The traffic data is current, but the mean response time has not updated for more than an hour. Which of the following is the best way to verify the data's freshness?

A. Testing for network connectivity issues
B. Checking the last time the calculation script ran
C. Refactoring the code base
D. Determining the number of calls with no timestamps

Answer: B

Explanation:
This question pertains to theData Governancedomain, which in DA0-002 includes ensuring data quality and freshness, especially in dashboards. The issue is that the mean response time isn't updating, while traffic data is current, indicating a potential issue with the data refresh process forthe response time metric.
* Refactoring the code base (Option A): Refactoring might improve long-term performance but doesn't directly address verifying data freshness.
* Testing for network connectivity issues (Option B): Network issues could cause delays, but since traffic data is updating, connectivity is likely not the issue.
* Checking the last time the calculation script ran (Option C): Mean response time is a calculated metric, likely derived from a script. Checking when the script last ran directly verifies if the data refresh process failed, making this the best approach.
* Determining the number of calls with no timestamps (Option D): Missing timestamps might indicate data quality issues, but it doesn't directly verify why the mean response time isn't updating.
The DA0-002 Data Governance domain focuses on "data quality control concepts," including ensuring data freshness in reporting. Checking the script's last run time aligns with this objective.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 74
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. Explode both tables to identify unique values and reorder the fields in one table.
C. Create a cluster to facilitate data integration between the tables.
D. Match the records of the related columns and merge the tables.

Answer: D

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 # 75
Which of the following elements is the most important to include in a dashboard for internal technical audiences?

A. Dynamic features
B. Company branding
C. Methodology section
D. Key performance indicators

Answer: D

Explanation:
This question pertains to theVisualization and Reportingdomain, focusing on dashboard design for specific audiences. Internal technical audiences (e.g., data analysts, IT staff) need actionable, data-driven insights.
* Methodology section (Option A): Methodology is important for research reports, not dashboards, especially for technical audiences who prioritize data.
* Dynamic features (Option B): Dynamic features (e.g., interactivity) are useful but not the most critical element for technical audiences.
* Key performance indicators (Option C): KPIs provide critical metrics (e.g., system uptime, error rates) that technical audiences need to monitor and act on, making this the most important element.
* Company branding (Option D): Branding is more relevant for external audiences, not internal technical ones.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and KPIs are essential for technical dashboards.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.

NEW QUESTION # 76
The human resources department wants to know the number of employees who earn $125,000 or more.
However, the department is concerned about duplicates in the dataset. Given the following table:
Employee_ID
Level
Salary
001
1
10000
002
2
20000
003
2
256000
004
2
125000
001
1
10000
002
2
20000
Which of the following SQL statements resolves this issue?

A. SELECT DISTINCT Employee_ID FROM Employee WHERE Salary >= 125000
B. SELECT DISTINCT Employee_ID FROM Employee WHERE Salary > 125000
C. SELECT COUNT(DISTINCT Employee_ID) FROM Employee WHERE Salary >= 125000
D. SELECT COUNT(Employee_ID) FROM Employee WHERE Salary >= 125000

Answer: C

Explanation:
This question falls under theData Analysisdomain, focusing on SQL queries to handle duplicates while counting employees. The task is to count unique employees with a salary of $125,000 or more, addressing duplicates in the dataset.
* Option A: SELECT DISTINCT Employee_ID FROM Employee WHERE Salary >= 125000This lists unique Employee_IDs but doesn't provide a count, which the department needs.
* Option B: SELECT COUNT(DISTINCT Employee_ID) FROM Employee WHERE Salary >=
125000This counts unique Employee_IDs (using DISTINCT) with a salary of $125,000 or more, correctly addressing duplicates and providing the required count (2 employees: 003 and 004).
* Option C: SELECT DISTINCT Employee_ID FROM Employee WHERE Salary > 125000This lists unique Employee_IDs with a salary strictly greater than $125,000 (missing 004), and doesn't provide a count.
* Option D: SELECT COUNT(Employee_ID) FROM Employee WHERE Salary >= 125000This counts all rows without addressing duplicates, resulting in an incorrect count (2 rows, but only 2 unique employees).
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and COUNT(DISTINCT) is the correct method to count unique employees while handling duplicates.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

NEW QUESTION # 77
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