This section introduces the key components and concepts of a model. The discussion of these components and concepts is done with little reference to using ModelBuilder, since the purpose is to inform you of these concepts so that the mechanics of using ModelBuilder becomes more natural and intuitive for you.
At the highest level, models contain only three things; elements, connectors, and text labels.
Elements are the data and tools you work with. Connectors are the lines that connect data to tools. Text labels can be associated with the entire model, individual elements, or individual connectors.
Learn more about ElementsLearn more about ConnectorsLearn more about text labels
Elements have their own labels, which are different from text labels, that you create and associate with models, elements, and connectors. A tool element, for example, is labeled with the name of the tool, but you can change this label.
Learn more about Element labels
A tool plus its data is called a process. Processes can be in different states: ready-to-run, has-been-run, and not-ready-to-run.
Learn more about processesLearn more about process states
Model parameters are data elements that you want to appear on the tool dialog so that a user can enter values for the data elements.
Learn more about model parameters
You can validate your model before executing. Validation will check for missing and incorrect data.
Learn more about validation
Some of the data created by models is intermediate, created only to feed into another tool and not needed after the model has been executed. You can declare that data elements are intermediate, and there are methods to delete intermediate data.
Learn more about intermediate data
In-line variable substitution is a technique that allows you to take values from one element and use them in another element. It is especially useful in situations such as constructing and using pathnames to data.
Learn more about in-line variable substitution
There are a few tools that cannot create complete output data elements until the tool is executed. When you use these tools in models, you need to understand the issues and the simple workarounds.
Learn more about incomplete output data elements