Mastering Data Validation with the Dell Boomi Cleanse Shape

In data integration, ensuring data quality and consistency is paramount. Dell Boomi’s Cleanse shape acts as your data guardian, allowing you to enforce rules and transform data, preventing errors and ensuring smooth integration processes. Let’s delve into how you can utilize this powerful shape.

What is the Cleanse Shape?

• The Cleanse shape is a logical shape within Dell Boomi processes.
• It validates data within a document against restrictions defined in a Boomi profile.
• The Cleanse shape can either:
  • Repair data that violates the limits (e.g., trimming strings, correcting data types)
  • Reject the entire document if validation fails, allowing it to be routed for error handling.

Why Use the Cleanse Shape?

1. Enforce Data Integrity: Ensure the data entering your integrations meets specific format and content requirements.
2. Prevent Downstream Errors: Proactively catch errors such as incorrect data types, missing fields, or unexpected formatting early in the process.
3. Centralized Validation: Create reusable profiles to establish consistent validation rules across multiple processes.

Using the Cleanse Shape: A Step-by-Step Guide

1. Create a Profile: Define the data structure and restrictions (data type, length, mandatory fields, regular expressions, etc.). Boomi supports profiles for various data formats, such as XML, JSON, CSV, and flat files.
2. Add the Cleanse Shape to Your Process: Drag and drop the shape into your Boomi process where data validation is needed.
3. Configure the Cleanse Shape:

• • Select the appropriate profile you created.
  • Choose between “Repair” or “Reject” behavior for invalid data.
  • Optionally select to trim leading and trailing spaces.

Example: Validating an XML Purchase Order

Suppose you receive purchase orders in XML format. Before integrating this data, you want to ensure:

• “OrderID” is mandatory and numeric.
• “OrderDate” follows the format YYYY-MM-DD.
• “Quantity” is a positive integer.

1. Profile Creation: Create an XML profile, define the structure of your purchase order, and apply the above restrictions.
2. Process Setup: Insert a Cleanse shape after your source connector. Configure it to use the XML profile and “Reject” invalid orders.

Best Practices

• Use with Maps: Cleanse shapes work well before Map shapes to ensure data is prepared for proper mapping and transformation.
• Reject for Critical Errors: For critical data issues, rejecting documents ensures they are handled through exception processes.
• Logging: Enable logging on the Cleanse shape to track document validation and errors.

Note: Although Boomi officially states that the Cleanse shape isn’t explicitly designed for JSON profiles, it can effectively validate JSON data in many instances.

In Conclusion

The Boomi Cleanse shape provides a robust mechanism for maintaining data quality within your integration flows. By understanding its functionality and following best practices, you can streamline your integrations and minimize potential errors downstream in your systems.