Input and Output Nodes: Add Data and Write to a Batch Data Transform

Add data to a batch data transform with an input node. To save batch data transform output, write your data to one or more output nodes. In Data 360, input and output nodes can be either data lake objects or data model objects of type Profile or Other. You can’t have a data lake object input node and a data model object output node, and vice versa. Typically data aware specialists and engineers have access to data lake objects and data model objects, whereas marketers and analysts have access only to data model objects.

• Add an Input Node to a Batch Data Transform
  Create an input node for each set of data that you want to add to the batch data transform. The batch data transform creates an input node when you initially select your input data, but to add more data you add another node.
• Write the Batch Data Transform Results to a Data Lake Object Output Node
  To use your batch data transform as input to identity resolution, calculated insights, or segmentation, you write the results to a new or existing data lake object (DLO) in an output node. The object that holds the output is called a target data lake object. You can’t save a batch data transform without an output node.
• Write the Batch Data Transform Results to a Data Model Object Output Node
  Write the results of a batch data transform to an existing data model object or one created through the output node. The object that holds the output is called a transform data model object. You can only write to a transform type data model object within a data transform. You can use a transform type data model object as input to another batch data transform and downstream processes such as identity resolution, calculated insights, and segmentation.
• Merge Records with Multi-Definition Transforms
  A transform definition specifies the sequence of operations applied to the data during a batch data transform. Definitions appears as nodes in the data flow canvas. You can combine multiple definitions to produce a single, unified output.
• Data Preview Sampling
  Use data preview sampling to see a more accurate picture of your data at each node in Preview. By widening the sample size and selecting the mode to arrange your data, data sampling helps prevent working without preview data. Select Filtered Rows to isolate specific values.