You have a data source which provides many fields needed for data scoring. Some of these fields are not needed after the scoring is complete for the rest of the stream to operate. Which node should…

The correct answer is B. Select node. Select node (B) is correct because it allows you to choose which fields to keep or drop from a data stream, making it ideal for removing unnecessary fields after scoring is complete - keeping the pipeline clean and efficient. Filter node (A) filters rows (records) based on…

Data Preparation

Question

You have a data source which provides many fields needed for data scoring. Some of these fields are not needed after the scoring is complete for the rest of the stream to operate. Which node should be used to remove these fields?

Options

AFilter node
BSelect node
CSample Node
DType node

How the community answered

(22 responses)

A
5% (1)
B
86% (19)
D
9% (2)

Explanation

Select node (B) is correct because it allows you to choose which fields to keep or drop from a data stream, making it ideal for removing unnecessary fields after scoring is complete - keeping the pipeline clean and efficient.

Filter node (A) filters rows (records) based on conditions, not columns/fields.
Sample node (C) reduces the number of rows by selecting a subset of records, not fields.
Type node (D) sets data types and roles for fields but does not remove them from the stream.

Memory tip: Think "Select = selecting columns" - just like a SQL SELECT statement picks which columns you want, the Select node picks which fields survive into the next stage of your stream.

Topics

#filter node#field removal#data stream#column selection

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