An analyst has created a bar chart showing sales by product category. The chart shows an unusually tall bar for one category. Before investigating the data, what should the analyst do to ensure the visualization is not misleading?

Immediately conclude that the category has the highest sales and move on to other analyses

Check the chart's axis scale and data labels to confirm the visualization is accurately representing the underlying values

Remove the category from the chart to make the other categories easier to compare

Change the chart type to a pie chart to see if the anomaly is still present

An analyst is troubleshooting a SQL query that is running very slowly. The analyst has already reviewed the query and the database schema. What is the most effective way to use online resources to find a performance solution?

Post the entire query on a general social media site and ask for help

Search for the specific database platform (e.g., 'SQL Server slow query performance') on a database administrator forum

Search for 'how to use a computer' to ensure basic skills are not the issue

Email the database vendor's CEO for a direct solution

An analyst is using a new R package for statistical analysis and encounters an error message that is not descriptive. The analyst is unfamiliar with the package's internal functions. Which approach is the most efficient way to find a solution?

Reinstall the R package and hope the error disappears

Rewrite the analysis code from scratch to avoid the problematic function

Post the error message on a general social media platform and wait for responses

Search the package's official documentation and its GitHub repository for issues or discussions related to the error

Two analysts are working on the same dataset to calculate the average order value. Analyst A gets a result of $150, and Analyst B gets a result of $125. They both confirm they are using the same source table. What is the most effective collaborative step to resolve this discrepancy?

Assume the data is corrupted and request a new data extract

Average the two results to get a compromise value of $137.50

Let the more senior analyst's result be the correct one

Have both analysts walk through their step-by-step processes together to compare their filtering, joining, and calculation logic

CompTIAData+

Domain 3Objective 3

Troubleshoot Analysis Issues DA0-001 Practice Questions (Page 6)

Part of the Data analysis domain, which accounts for 24% of the DA0-001 exam. CompTIA does not publish an official question count, but from its 90-minute exam (~35–60 total, ~8–14 in this domain), expect 3–5 from this objective — we provide 32 practice questions to prepare you well beyond it. (estimate)

32questions here

7free pages

7concepts

24%of the exam

Questions 26–30

26application · medium
An analyst has created a bar chart showing sales by product category. The chart shows an unusually tall bar for one category. Before investigating the data, what should the analyst do to ensure the visualization is not misleading?
Select an answer first
27foundation · easy
An analyst is using a data analysis tool and receives an error indicating that a formula contains an invalid reference. Which feature should the analyst use to identify the exact cell or range causing the problem?
Select an answer first
28application · medium
An analyst is troubleshooting a SQL query that is running very slowly. The analyst has already reviewed the query and the database schema. What is the most effective way to use online resources to find a performance solution?
Select an answer first
29application · medium
An analyst is using a new R package for statistical analysis and encounters an error message that is not descriptive. The analyst is unfamiliar with the package's internal functions. Which approach is the most efficient way to find a solution?
Select an answer first
30expert · hard
Two analysts are working on the same dataset to calculate the average order value. Analyst A gets a result of $150, and Analyst B gets a result of $125. They both confirm they are using the same source table. What is the most effective collaborative step to resolve this discrepancy?
Select an answer first

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