Which node do you use to cleanse a dataset by removing duplicate records?

The Distinct node is designed specifically to identify and remove duplicate records from a dataset. This functionality is essential in data preprocessing as duplicate entries can lead to misleading analysis and inaccurate model predictions. When the Distinct node is applied, it scans through the dataset and filters out any rows that are exact duplicates, effectively ensuring that each entry in the resulting dataset is unique.

The other options serve different purposes:

• The SetToFlag node is used for flagging records based on specific criteria rather than removing duplicates.

• The Aggregate node is typically employed to summarize data by grouping it and performing calculations such as sums or averages, but it does not specifically target duplicates for removal.

• The Matrix node is utilized for creating matrix structures for analysis rather than for cleansing or deduplication tasks.

Hence, the Distinct node is the appropriate choice when the goal is to cleanse a dataset by eliminating duplicate records.