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The base dataset in this example is a collection of customer records. It has the following fields:

• $customer_id
• $firstname
• $lastname
• $create_time

The reference dataset is a collection of transactions made by the customers listed in the base dataset. It has the following fields:

• $transaction_id
• $customer_id
• $source
• $num_item
• $total 

Both datasets are provided by the CSV Generator Snaps titled Customers and Transactions. These are passed through a Type Converter Snaps so that all data types are mapped correctly. This is required to enable the Feature Synthesis Snap to generate features accurately. 

A preview of the customer and transaction datasets that are output by the CSV Generator Snaps is as shown below:

The field $customer_id is common between both datasets. The Feature Synthesis Snap will use this field to join datasets and is configured as shown below:

The customer dataset is connected to the first input view (titled customer); so this view becomes the Base view. Similarly, the transaction dataset is connected to the second input view (titled transaction); so that becomes the Ref view.

Upon successful execution, the Feature Synthesis Snap generates features and adds them to the base dataset as shown below: 

The same output is shown in a JSON format to let you see the full list of features:

Download this Pipeline.