A data analyst is reviewing a dataset for a predictive maintenance model. The 'temperature' column contains values that fluctuate randomly due to sensor noise. The analyst wants to reduce the impact of this noise without losing the underlying trend. Which technique is most appropriate?

Replace noisy values with the median of the entire column

Apply a moving average to smooth the temperature readings

Duplicate the noisy rows to increase their weight

A financial institution has a model that approves loan applications. The model was trained on historical data, but the data pipeline now occasionally introduces records with missing income values and inconsistent date formats. The compliance team requires that data quality issues be detected and reported promptly. Which monitoring approach best meets this requirement?

Perform a quarterly manual audit of the data

Monitor only the model's accuracy metric

Set up automated checks that validate schema, missing values, and format consistency on each batch of data

Wait for customer complaints to identify data issues

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Domain 4Objective 4

Dataset Quality Issues CT-AI Practice Questions (Page 4)

Part of the Domain 4: ML - Data domain, which makes up ~12% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~3–5 in this domain), expect 1–1 from this objective — we provide 26 practice questions to prepare you well beyond it. (estimate)

26questions here

6free pages

6concepts

Questions 16–20

16application · medium
A data analyst is reviewing a dataset for a predictive maintenance model. The 'temperature' column contains values that fluctuate randomly due to sensor noise. The analyst wants to reduce the impact of this noise without losing the underlying trend. Which technique is most appropriate?
Select an answer first
17foundation · easy
Which data quality dimension refers to the degree to which data correctly reflects the real-world entity or event it is supposed to represent?
Select an answer first
18application · medium
A data scientist is working with a dataset that contains a 'salary' column. The data scientist suspects that some values are implausibly high due to data entry errors. Which visualization technique is most effective for identifying these extreme values?
Select an answer first
19foundation · easy
Which of the following is a data quality assessment technique that uses graphical representations to identify patterns, trends, and anomalies in the data?
Select an answer first
20application · medium
A financial institution has a model that approves loan applications. The model was trained on historical data, but the data pipeline now occasionally introduces records with missing income values and inconsistent date formats. The compliance team requires that data quality issues be detected and reported promptly. Which monitoring approach best meets this requirement?
Select an answer first

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Dataset Quality Issues CT-AI Practice Questions (Page 4)

Questions 16–20

A data analyst is reviewing a dataset for a predictive maintenance model. The 'temperature' column contains values that fluctuate randomly due to sensor noise. The analyst wants to reduce the impact of this noise without losing the underlying trend. Which technique is most appropriate?

Which data quality dimension refers to the degree to which data correctly reflects the real-world entity or event it is supposed to represent?

A data scientist is working with a dataset that contains a 'salary' column. The data scientist suspects that some values are implausibly high due to data entry errors. Which visualization technique is most effective for identifying these extreme values?

Which of the following is a data quality assessment technique that uses graphical representations to identify patterns, trends, and anomalies in the data?

Keep studying — Domain 4: ML - Data