Data Mocking

Data mocking involves the simulation or fabrication of data, serving as a valuable tool during the development of a workflow.

Benefits:

• Minimize the frequency of querying your data source in order to optimize efficiency and reduce expenses.

• Engage with a limited and consistent dataset in the early stages of the development process.

• To avoid the possibility of overwriting current data, it is advisable to refrain from linking actual data sources during the initial phases of constructing your workflow.

Mocking with real data using data pinning

By employing data pinning, real data is inserted into your workflow and then pinned in the output panel of a particular node. This method allows for the acquisition of accurate data with just a single query to the data source, enabling the editing of pinned data. Use this method to set up your workflow for the specific data structure and parameters from your data source.

Generate custom data using the Code or Edit Fields nodes

You can create a custom dataset in your workflow using either the Code node or the Edit Fields (Set) node.

In the Code node, you can create any data set you want, and return it as the node output. In the Edit Fields node, select Add fields to add your custom data. The Edit Fields node is a good choice for small tests. To create more complex datasets, use the Code node.

Output a sample data set from the Customer Datastore node

The Customer Datastore node offers a simulated dataset for analysis purposes. By incorporating and running this node, users can delve into the data. Employ this method if you require test data while familiarizing yourself with Appizap Workflow Builder, and lack a use-case to work.