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Answer: Apply SQL Transformation
The question requires adding a new column named 'CityName' with a constant value 'London' for all rows. The 'Apply SQL Transformation' module (Option D) is the correct choice because it allows executing SQL queries to add new columns and populate them with constant values (e.g., using `SELECT *, 'London' AS CityName FROM dataset`). This is supported by the community consensus (82% selected D), with highly upvoted comments explaining that SQL transformation efficiently handles this task. Option B ('Edit Metadata') is incorrect, as it only modifies existing column properties (e.g., data types or names) but cannot add new columns or set their values. Options A and C are unrelated: 'Extract N-Gram Features' is for text analysis, and 'Preprocess Text' cleans text data, neither of which addresses adding a constant-value column.
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You are performing feature engineering on a dataset. You need to add a new column named CityName where every row has the value "London". Which module in Azure Machine Learning Studio should you use?
A
Extract N-Gram Features from Text
B
Edit Metadata
C
Preprocess Text
D
Apply SQL Transformation
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