Description:

This step assigns unique GUID values to a specified column within an ETL dataset.

The Set GUID Identity Column ETL step generates a new globally unique identifier (GUID) for each processed row and assigns it to the selected column. This enables workflows to create unique identifiers for imported or transformed records before loading them into destination systems.

The generated GUID values are unique across all records and can be used as primary keys, unique identifiers, integration keys, or reference values during ETL processing.

This step provides an efficient way to automate identity generation without relying on database-generated identity columns.

The step supports:

• Automatic GUID generation
• Identity assignment for every processed row
• Configurable destination column
• Integration with FlowWright ETL pipelines
• Automatic unique record identification

This step can be used for:

• ETL data migration
• Database imports
• Primary key generation
• Data warehouse loading
• System integration
• Master data management
• Business process automation

Usage:

The Set GUID Identity Column step is typically placed immediately before inserting records into a destination database or exporting transformed data.

The ETL pipeline generates a unique GUID for each processed row and stores it in the specified destination column before subsequent transformation or load operations execute.

A typical ETL workflow might look like this:

Once the GUID values have been generated, later ETL steps can:

• Map destination fields
• Insert records into databases
• Export transformed datasets
• Create relationship mappings
• Synchronize external systems
• Continue ETL processing

The destination column should exist within the ETL dataset before this step is executed.

Prerequisite:

The ETL process engine service should be running to execute the ETL definitions.

Example:

Let’s build and execute the “clsGUIDIdentityDef” example.          

• Create a new ETL definition named “clsGUIDIdentityDef” and open it in designer mode.
• Drag “clsInputCSV, clsGUIDIdentity, clsTransformReplaceText, and clsOutputCSV” steps to the canvas. 
• Connect the dots between the “Start” and other steps, as shown above.
• Define any variables or globals required for execution.
• Click the "clsInputCSV" step to configure its "Required" properties. Provide a name for the step. Specify the path to the input CSV file on the application server. Select the ETL data schema from the drop-down list. Note: The schema's column names should match those in the input file. Click the Save button. Click here to learn about the ETL Data Schema Designer.

• Click the "clsInputCSV" step to configure its "Optional" properties. Select the Show Schema button. The pop-up window displays the schema columns as shown below. This function helps to understand the schema at a glance.  

• Click the "clsGUIDIdentity" step to configure its "Required" properties. Provide a name for the step. Specify the name of the column to set as the GUID identity. Click the Save button. 

• The “Logging” configuration is necessary for documentation and also measures workflow progress and percent complete. This is achieved by configuring the step state and percent fields individually, as shown below. Configure the “Logging” using the following properties.

• Click the "clsTransformReplaceText" step to configure its "Required" properties. Provide a name for the step. Click the button to configure the columns to transform. Then click the Save button. 

• Click the "clsTransformReplaceText" step to configure its "Required" properties. Click the button to open the transform list configuration window. Click the Add Row (+) button to insert an empty row. Select the text column from the drop-down list. Enter the “find word” and “replace word” in the transformation columns. Select the checkbox to replace the field value. Click the Save button. You may add multiple columns for transformation by using the Add Row button.  

• Click the "clsOutputCSV" step to configure its "Required" properties. Enter a name for the step. Enter the path to the output CSV file on the application server. Click the Save button. 

• Click the "clsOutputCSV" step to configure its "Optional" properties. Provide a name for the step. Provide the variable or global reference to store the virtual output path. Click the Save button. 

• Save the ETL Definition. Execute the ETL process. When the ETL pipeline reaches the Set GUID Identity Column step, FlowWright generates a new GUID value for every processed record and stores it in the configured destination column. After the GUID values have been assigned, ETL processing automatically continues to the next transformation or destination step. Verify the processed dataset to confirm that each record contains a unique GUID value in the configured column.

• The ETL transform pivot output file is included here for reference.

Tips:

• Ensure that the specified column exists within the ETL dataset before executing the process.
• Use GUID values when records require globally unique identifiers across multiple systems.
• Configure this step before inserting records into destination databases that expect GUID primary keys.
• Use meaningful column names such as RecordID, CustomerGUID, or TransactionID.
• Avoid overwriting existing identity values unless replacement is intentional.
• Combine this step with Column Mapping, Data Transformation, Database Insert, Lookup, or Export ETL steps to automate complete data migration workflows.

Notes:

• A new GUID is generated independently for every processed row.
• Generated GUID values are globally unique and suitable for distributed systems.
• The destination column should be capable of storing GUID values.
• Existing column values may be replaced if the configured column already contains data.
• The ETL process should validate destination schema compatibility before loading records.
• GUID generation occurs entirely within the ETL pipeline and does not require database identity columns.
• This step is intended for ETL workflows and does not define True or False workflow return paths.

Definition Sample:

You may download the sample definition(s) from the link provided and later import them (drag-and-drop) into your FlowWright ETL Definition page.

Note: Verify and complete any missing configuration after importing the sample, including:

• Destination column name
• Source dataset configuration
• Column mappings
• Destination database schema
• ETL transformation settings
• Environment-specific settings

After verifying the configuration, save the ETL Definition before execution.

Click here to download the sample file.