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Data Acquisition and PreparationhardMultiple ChoiceObjective-mapped

DA0-002 Data Acquisition and Preparation Practice Question

Exhibit

Refer to the exhibit.
ERROR: Data type mismatch for column 'transaction_amount' at row 342. Expected DECIMAL(10,2), received VARCHAR.
The source system sends transaction_amount as a string with a currency symbol (e.g., '$123.45').

A data pipeline log shows the above error. Which data transformation should be applied during acquisition?

⚠ Common exam trap

Watch out — candidates often assume CAST in SQL can handle any string-to-number conversion, but CAST strictly requires a valid numeric string and will throw an error for non-numeric characters, making preprocessing essential.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Preprocess the string to remove non-numeric characters, then convert to DECIMAL

The error indicates that the pipeline encountered a string with non-numeric characters (e.g., '$1,234.56') when trying to load it into a DECIMAL column. Preprocessing the string to remove non-numeric characters (like currency symbols, commas) before conversion ensures the data is clean and parseable, which is a standard data transformation during acquisition to handle dirty source data.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Skip rows that cause errors

    Why it's wrong here

    Skipping rows leads to data loss.

  • Preprocess the string to remove non-numeric characters, then convert to DECIMAL

    Why this is correct

    Removing symbols before conversion ensures successful casting.

  • Use CAST(transaction_amount AS DECIMAL(10,2)) in SQL

    Why it's wrong here

    CAST will fail because the string contains '$'.

  • Change the target column type to VARCHAR

    Why it's wrong here

    This avoids the error but loses the ability to perform numeric operations.

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