Data Prep allows data engineers to map, transform, and validate data to and from Experience Data Model (XDM). Data Prep appears as a "Map" step in the Data Ingestion processes, including CSV Ingestion workflow. Data engineers can use Data Prep to perform the following data manipulation during ingestion:
- Define simple pass-through mappings to assign input attributes to XDM attributes
- Create calculated fields to perform in-row calculations that can be assigned to XDM attributes
- Transform the data by applying string, numeric, or date manipulation functions
- Construct XDM hierarchies using hierarchical functions
- Preview the data as it is manipulated within the Data Prep
Data Prep also applies several intrinsic data validations to ensure that the data integrity is maintained as it is ingested. Where possible, Data Prep automatically maps the incoming data schemas to XDM. Data engineers can change, correct, and delete the suggested mappings and replace them with the mappings as appropriate.
A mapping is an association of an input attribute or calculated field to one XDM attribute. A single attribute can be mapped to multiple XDM attributes by creating individual mappings.
To learn more about the different mapping functions, please read the mapping functions guide .
A set of mappings that transform one schema to another are collectively known as a mapping set. A single mapping set is created as part of each data flow. A mapping set is an integral part of the data flows and is created, edited, and monitored as part of the data flows.