A data engineer is cleaning a dataset for a sentiment analysis model. The dataset contains multiple entries for the same user review, and some reviews have been truncated, resulting in incomplete text. The engineer wants to ensure each review appears only once and that the text is complete. Which sequence of actions is most appropriate?

First deduplicate the reviews, then remove truncated entries

First remove truncated entries, then deduplicate

Why can poor data quality lead to an ML model that underperforms on new, unseen data even if it performs well on the training data?

Because the model's hyperparameters are not tuned correctly.

Because the model may learn spurious patterns that are specific to the errors in the training data, which do not generalize.

Because poor data quality always causes the model to underfit, resulting in poor performance on both training and test data.

Because the model is not complex enough to capture the patterns in the data.

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Domain 4Objective 4

Dataset Quality Issues CT-AI Practice Questions (Page 5)

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 21–25

21application · medium
A marketing team is building a model to predict customer lifetime value. The dataset includes purchase history from the last 5 years, but the company's product line has changed significantly in the last year. The team includes all historical data without considering the changes. Which data quality dimension is most likely to be compromised?
Select an answer first
22foundation · easy
Which data cleaning strategy involves replacing missing values with a substituted value, such as the mean or median of the column?
Select an answer first
23application · medium
A logistics company is building a model to predict delivery delays. The dataset includes a 'delivery_time' column that is recorded in different time zones, and some entries are missing. The team wants to ensure the model is trained on data that is both consistent and complete. Which data quality dimensions are most directly addressed by standardizing time zones and filling missing values?
Select an answer first
24application · medium
A data engineer is cleaning a dataset for a sentiment analysis model. The dataset contains multiple entries for the same user review, and some reviews have been truncated, resulting in incomplete text. The engineer wants to ensure each review appears only once and that the text is complete. Which sequence of actions is most appropriate?
Select an answer first
25foundation · easy
Why can poor data quality lead to an ML model that underperforms on new, unseen data even if it performs well on the training data?
Select an answer first

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Dataset Quality Issues CT-AI Practice Questions (Page 5)

Questions 21–25

Which data cleaning strategy involves replacing missing values with a substituted value, such as the mean or median of the column?

Why can poor data quality lead to an ML model that underperforms on new, unseen data even if it performs well on the training data?

Keep studying — Domain 4: ML - Data