Description:

The CSV Output File step is an ETL destination component that writes processed datasets into a CSV file.

CSV is one of the most widely supported formats for data exchange because it is simple, compact, and compatible with virtually every database, spreadsheet application, analytics platform, and enterprise integration tool. The CSV Output File step enables FlowWright ETL pipelines to generate CSV files without requiring custom scripting or external utilities.

The step is configured by specifying:

• The output CSV file location
• An optional workflow variable or global variable that stores the generated virtual file path

During execution, the ETL engine processes each incoming row and writes it as a comma-separated record while preserving the column order established by upstream ETL transformations.

The optional Variable/Global to Hold Virtual Path property allows subsequent workflow activities to reference the generated CSV file without hard-coding its location. This is particularly useful when the exported file must be attached to emails, uploaded to a document management system, transferred to an FTP location, or processed by downstream workflow steps.

The CSV Output File step is typically the final component in an ETL pipeline.

The step supports:

• CSV file generation
• Enterprise data export
• Lightweight data exchange
• Business reporting
• Virtual path storage
• Integration with FlowWright ETL pipelines

Typical business uses include:

• Customer data exports
• Sales reporting
• Financial data exchange
• ERP imports
• CRM synchronization
• Data warehouse staging
• Third-party system integrations

Usage:

The CSV Output File step is typically the final component in an ETL definition.

During execution:

1. The incoming dataset is received from upstream ETL components.
2. Each record is converted into a comma-separated row.
3. The completed CSV file is written to the configured output location.
4. If configured, the generated file's virtual path is stored in the specified workflow variable or global variable.
5. ETL execution completes successfully.

A typical ETL pipeline might look like this:

Typical usage scenarios include:

• Exporting customer master records
• Producing daily sales extracts
• Creating inventory import files
• Sharing operational reports
• Preparing datasets for business intelligence platforms
• Delivering files to external business partners
• Archiving processed enterprise data

The generated CSV file can then be imported into Microsoft Excel, SQL Server, reporting tools, analytics platforms, ERP systems, CRM applications, or other enterprise software.

Prerequisite:

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

Example:

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

• Create a new ETL definition named “clsInputCSVDef” and open it in designer mode. 
• Drag “clsInputCSV, clsTransformFormatStringToNumber, and clsOutputCSV” steps to the canvas. 
• Connect the dots between the “clsInputCSV”  step and other steps, as shown above.
• Define a variable or a global 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 view 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 "clsTransformFormatStringToNumber" step to configure its "Required" properties. Provide a name for the step. Click the button to configure the transform list, then click the Save button. 

• Click the "clsTransformFormatStringToNumber" step to configure the transform list. The configuration pop-up window appears. Click the Add Row (+) button to insert an empty row. Select the string as the input source column and the integer/value as the output target column. 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 and specify the variable or global reference to hold the virtual output path. 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.

• Save the ETL definition, create a new instance, and execute it. Render the ETL instance. Click Items > Variables to view the variable values. The “clsInputCSV” step handles the transformation of the input file. The variable or global reference contains the output file’s virtual path, as shown below. 

Tips:

• Verify that the destination folder exists and that the FlowWright ETL service account has write permissions.
• Use descriptive file names that include reporting periods or business identifiers.
• Store the generated virtual path when subsequent workflow steps need to email, archive, upload, or process the CSV file.
• Validate the dataset before exporting to reduce downstream corrections.
• Export only the required columns to keep files compact and easy to consume.
• Maintain consistent column ordering across recurring exports to simplify downstream integrations.
• Combine this step with Validate Data, Transform Text Case, Transform Date by Format, Sorting Transform, Filter with Conditions, CSV Input File, SQL Input File, or Group By Transform to build complete enterprise ETL workflows.

Notes:

• The output path must be accessible to the FlowWright ETL server.
• The generated CSV file reflects the structure and column order of the incoming ETL dataset.
• The optional workflow variable or global variable stores the generated file's virtual path for use by subsequent workflow activities.
• File permission issues or invalid output paths may prevent successful file generation.
• Because this is an ETL destination component, it has no outgoing connections.
• File creation status and any execution errors are recorded in the ETL execution log.
• This step is commonly used for enterprise integrations, data migration, business reporting, financial exports, operational reporting, customer data exchange, regulatory submissions, and business intelligence.

CSV Output File vs. Excel Output File:

Both components export ETL datasets, but they are intended for different business and integration scenarios.

As a general guideline:

• Use CSV Output File when creating files for system integrations, database imports, analytics platforms, or high-volume data exchange.
• Use Excel Output File when producing reports intended for business users, management, or spreadsheet-based analysis.

Definition Sample:

You may download the sample ETL definition(s) from the link provided and later import them into your FlowWright ETL Designer.

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

• Output file location
• Destination folder permissions
• Workflow variable or global variable (if required)
• File naming conventions
• Environment-specific file paths
• Downstream workflow configuration

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

Click here to download the sample file.