Skip to content
Nappai Documentation

Merge Data

The Merge Data component takes several pieces of data and combines them into one single data object. It’s useful when you have data coming from different sources or steps in your workflow and you want to work with it as a single set.

How it Works

When you drop this component into your dashboard, it looks at the list of data objects you feed into it.

  • If you give it nothing, it simply returns an empty data object.
  • If you give it only one data object, it returns that object unchanged.
  • If you give it two or more, it adds them together one by one. The “+” operation for data objects is defined by the system to merge the contents, so the final result contains all the information from every input.

No external services are called – everything happens locally inside the Nappai engine.

Inputs

  • Data Inputs: A list of Data inputs objects to be merged.
  • Join Type: Type of join to perform when combining by key.
  • Key Field: Field name(s) to use as key for grouping data objects.
  • Merge Type: The type of merge to be performed.

Outputs

  • Merged Data: The combined data object that results from merging all the inputs. This output can be used as the input for other components that need a single, unified data set.

Usage Example

  1. Collect Data – Use separate components to pull data from a database, an API, and a CSV file.
  2. Merge Data – Connect the outputs of those components to the Data Inputs field of the Merge Data component.
  3. Continue Workflow – Feed the Merged Data output into a filtering or transformation component to process the combined data further.

This simple flow lets you bring together information from multiple sources and treat it as one dataset for the rest of your automation.

  • Split Data – Break a single data object into multiple parts.
  • Filter Data – Keep only the rows that meet certain conditions.
  • Transform Data – Apply calculations or format changes to your data.

Tips and Best Practices

  • Check Compatibility: Make sure the data objects you merge have compatible structures; otherwise the merge may produce unexpected results.
  • Use Merge Type Wisely: If you need to keep duplicate rows, choose a merge type that preserves them; if you want to eliminate duplicates, select a deduplication merge type.
  • Keep It Simple: For large datasets, consider merging in stages (e.g., merge two at a time) to avoid performance bottlenecks.
  • Validate Early: Add a quick “Print Data” component after merging to confirm the result before moving on.

Security Considerations

The Merge Data component only processes data that is already in the workflow; it does not access external networks or store data outside the Nappai environment. Ensure that any sensitive data is handled according to your organization’s privacy policies before feeding it into this component.