How to Use the Data Process Connector in Boomi

The Data Process connector in Boomi is a powerful tool that enables users to manipulate and transform data within an integration process. With its flexible configuration options, it is a cornerstone for achieving complex data transformations without requiring external scripts or custom coding.

Key Features of the Data Process Connector

The Data Process connector supports a range of operations, such as splitting documents, merging data, encoding/decoding, compression, and data transformation using scripting. It provides pre-configured actions that simplify common tasks, like converting CSV files to XML or performing batch processing.

Setting Up the Data Process Connector

1. Add the Connector: Drag the Data Process shape from the component palette to your integration process in the Boomi Process canvas.
2. Configure Action: Open the shape’s properties and choose the desired action, such as splitting, combining, or scripting. Each action has its unique configuration options tailored to its functionality.

Common Use Cases

1. Splitting Data: Break a single document into smaller documents based on a delimiter, fixed record size, or custom script. This is useful for processing batch files.
2. Combining Data: Merge multiple documents into one for streamlined downstream processing.
3. Custom Scripts: Use Groovy, JavaScript, or Boomi’s proprietary scripting language to handle unique data transformation needs, such as reformatting fields or adding custom logic.
4. Sorting: Reorganize document data based on specified criteria, improving consistency and data quality.
5. Base64 Encoding/Decoding: Handle secure data encoding needs for sensitive data exchange.

Step-by-Step Example: CSV to XML Conversion

1. Add the Data Process Shape: Drag it into your process flow and set the action to “Custom Scripting.”
2. Upload Script: Write or upload a Groovy or JavaScript code snippet to convert the CSV file into an XML format.
3. Test the Output: Run the process with sample data to validate that the transformation works as expected.

Best Practices

• Optimize Scripts: Keep custom scripts concise and well-documented for easier troubleshooting.
• Leverage Pre-Built Functions: Use Boomi’s out-of-the-box actions like splitting or sorting before resorting to scripting.
• Validate Data: Use a Test Shape to verify data transformations at different stages of the process.
• Error Handling: Implement try-catch blocks in scripts to handle unexpected errors gracefully.

Conclusion

The Data Process connector is indispensable for complex integrations in Boomi. Its versatility in handling a wide range of data manipulation tasks ensures that you can build robust and scalable integration processes. Whether splitting large files, encoding data, or performing custom transformations, the Data Process connector provides the tools you need to succeed in your integration projects.