Merge Data

The Merge Data component lets you combine several data sets into one.
You can simply stack them, join them on common fields, or merge them into a single record.

How it Works

When you feed the component a list of Data objects, it first checks the chosen Merge Type:

1. Append – All data objects are concatenated into one big list.
2. Combine by Key – The component groups rows that share the same value(s) in the Key Field.
   • INNER JOIN keeps only rows that have matching keys in every input.
   • OUTER JOIN keeps every row, filling missing values with empty strings.
3. Combine by Index – All data objects are merged into a single combined object, aligning rows by their position.

During the merge, any missing keys are automatically filled with empty strings so that every output row has the same set of columns.

Inputs

Input Fields

The following fields are available to configure this component. Each field may be visible in different operations:

• Data Inputs: A list of Data objects that you want to merge.

  • Visible in: All

• Join Type: The type of join to perform when combining by key. Choose INNER JOIN or OUTER JOIN.

  • Visible in: All

• Key Field: The field name(s) to use as the key for grouping data objects.

  • Visible in: All

• Merge Type: The type of merge to be performed. Options are Append, Combine by Key, or Combine by Index.

  • Visible in: All

Outputs

• Merged Data: A single Data object that contains the result of the merge.
  This output can be fed into other components such as filtering, transformation, or export.

Usage Example

Suppose you have two tables of customer information:

id	name	email
1	Alice	alice@example.com
2	Bob	bob@example.com

id	phone
1	555‑1234
3	555‑5678

1. Drag the Merge Data component onto the canvas.
2. Set Merge Type to Combine by Key.
3. Set Join Type to INNER JOIN (only customers that appear in both tables will stay).
4. Set Key Field to id.
5. Connect the two tables to Data Inputs.
6. The component outputs a merged table that contains only the record for id = 1.

You can then pass Merged Data to a Transform Data component to add new columns, or to an Export Data component to save the result.

Related Components

• Filter Data – Keep only rows that meet certain conditions.
• Transform Data – Add, modify, or delete columns.
• Split Data – Divide a single data set into multiple parts.
• Export Data – Save data to files or databases.

Tips and Best Practices

• Match Key Fields – Ensure that the key field names are identical in all input data sets.
• Use OUTER JOIN for Completeness – If you want to keep every record, choose OUTER JOIN; missing values will appear as empty strings.
• Check Column Consistency – After merging, verify that all expected columns are present.
• Keep Data Size Manageable – Large data sets can slow down the merge; consider filtering or splitting before merging.

Security Considerations

The Merge Data component processes data locally within the Nappai environment and does not call external APIs.
No sensitive data is transmitted outside the system, so standard data‑privacy practices for your organization apply.