Components > Intelligent structure models > Intelligent structure model example

Intelligent structure model example

Intelligent Structure Discovery creates an intelligent structure model based on the structure of the input data that you provide.
As an example, you want to create a model for a CSV input file that contains the following content:
Carrine,Stone,17 Torrence Street,Livingston,PA,10173
Poona,Tillkup,52 Perez Avenue,Livingston,PA,10256
Tasha,Herrera,158 Shiraz Boulevard,Kensington,WA,33823
John,Washington,22A Zangville Drive,Tucson,AZ,20198
Jane Hochuli 4483 Central Street Suite 30 Phoenix PA 38721
The following image shows the structure that Intelligent Structure Discovery discovers based on the input file:
This image shows a sample discovered structure with a hierarchy of nodes. In the top row, table is the parent of address. In the second row, address is the parent of fullName, street, city, state, and zip. In the third row, fullName is the parent of first and last.
You can see that Intelligent Structure Discovery created nodes representing the fields in the input file, such as first, last, street, city, state, and zip.
The structure represents not just the data fields themselves, but also the relationship of the fields to each other. For example, Intelligent Structure Discovery recognized that the data Carrine,Stone represents the first name and last name of a person. The nodes first and last are grouped together under the node fullName, representing the relationship of the data with each other.
Intelligent Structure Discovery also recognized that the data as a whole represented addresses. The data is grouped under a parent node address.
The nodes represent fields that are part of the output. Nodes that are related are grouped into an output group. Output groups can contain one or more nodes.