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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. Filter the data in the dashboard.
B. Confirm the dashboard is pointed to the newest dataset.
C. Escalate user permissions on the server.
D. Verify that the dashboard subscription is not expired.
Answer: B
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 # 27
A data analyst is gathering data from multiple tables in a database. The analyst needs certain columns from each table. Which of the following is the best method to accomplish this task?
A. Union
B. Aggregate
C. Nest
D. Join
Answer: D
Explanation:
This question falls under theData Acquisition and Preparationdomain, focusing on combining data from multiple tables. The analyst needs specific columns from each table, suggesting a method to combine data horizontally based on relationships.
* Aggregate (Option A): Aggregation (e.g., SUM, COUNT) summarizes data, not suitable for combining columns from tables.
* Union (Option B): Union stacks tables vertically, requiring identical structures, but the analyst needs specific columns, likely based on relationships, not a vertical stack.
* Nest (Option C): Nesting is used for hierarchical data (e.g., JSON), not for combining relational tables.
* Join (Option D): A join (e.g., INNER JOIN) combines tables horizontally based on a common key, allowing the analyst to select specific columns from each table, which fits the task.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and joining tables is the best method for combining specific columns from multiple tables.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.
NEW QUESTION # 28
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. Mean and median
B. Boolean data and an array
C. Standard deviation and constraints
D. Numerical and ordinal attributes
Answer: D
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 # 29
A data analyst needs to create a report that anticipates the number of calls received daily. Which of the following is the best statistical method to use?
A. Descriptive
B. Inferential
C. Diagnostic
D. Predictive
Answer: D
Explanation:
This question falls under theData Analysisdomain, focusing on statistical methods for forecasting. The task is to anticipate (predict) the number of daily calls, which involves looking into the future.
* Predictive (Option A): Predictive analytics uses historical data to forecast future outcomes (e.g., number of calls), which matches the requirement.
* Diagnostic (Option B): Diagnostic analytics identifies causes and patterns in historical data, not future predictions.
* Inferential (Option C): Inferential statistics make generalizations about a population, not specific forecasts.
* Descriptive (Option D): Descriptive analytics summarizes past data, not suitable for anticipating future values.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and predictive analytics is the best method for forecasting future call volumes.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 30
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. Validate that the database is up-to-date.
B. Check that the program is updated to the latest version.
C. Review the data layer and data source.
D. Ensure the correct filters are displaying on the dashboard.
Answer: C
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 # 31
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