Understand Batch Processing
Upload a CSV, pick your process, and receive a validated output file — no SFTP, no setup.
Use this article if you need to understand how DQVerify processes data files through the Standalone Interface. The DQE standalone application is integrated directly into DQVerify — qualify your data without going through the API and without any SFTP setup.
This article covers file-based batch processing. It does not apply to real-time API calls.
What batch processing does
When you submit a file to DQVerify's batch pipeline, records are processed according to your project configuration. The service can perform any combination of the following operations:
- Postal address standardization
- Deduplication
- Data enrichment
- Move detection
- Data cleaning
- Field standardization
How the process works
- 1
Prepare your CSV file using the expected format.
- 2
Upload the CSV file through the DQVerify Standalone Interface.
- 3
Pick the process — select which data quality services to apply.
- 4
DQVerify runs the processing and validation chain on your records.
- 5
Your processed file is automatically downloaded. A manual download button is also available if needed.
Processing flow
Example input and output
Your original data is returned unchanged. DQVerify appends result columns to the right. Select a service to see an example.
Input file
| ID | FIRSTNAME | LASTNAME | ADDRESS | CITY | STATE | ZIP |
|---|---|---|---|---|---|---|
| 1 | John | Smith | 123 Main St | Charlotte | NC | 28202 |
| 2 | Jane | Doe | 456 Oak Ave Apt 3 | Raleigh | NC | 27601 |
| 3 | Bob | Johnson | 789 Elm Stret | Durham | NC | 99999 |
Processed output — DQE columns highlighted
| ID | FIRSTNAME | LASTNAME | ADDRESS | CITY | STATE | ZIP | DQE_ADR4 | DQE_CP | DQE_VILLE | DQE_STATUT_RNVP | DQE_CQ_ADRS | DQE_ERROR |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | John | Smith | 123 Main St | Charlotte | NC | 28202 | 123 MAIN ST | 28202 | CHARLOTTE | OK NON-MODIFIEE | 10 | OK |
| 2 | Jane | Doe | 456 Oak Ave Apt 3 | Raleigh | NC | 27601 | 456 OAK AVE APT 3 | 27601 | RALEIGH | OK MODIFIEE | 22 | OK |
| 3 | Bob | Johnson | 789 Elm Stret | Durham | NC | 99999 | 789 ELM ST | 27701 | DURHAM | KO MODIFIEE | 70 | KO |
Row 2: street number confirmed despite missing confirmation — address modified. Row 3: street name typo corrected; postal code / city mismatch detected.
Input file requirements
Files submitted to the batch pipeline must meet the following format requirements. Files that do not conform will be rejected before processing begins.
Output file
DQVerify returns your original data unchanged, with additional columns appended for each service that ran. These added columns carry: validation status, standardized and corrected values, records requiring review, error and quality codes, and any enrichment data sourced during processing. The output file uses the same separator and encoding as the input file.
Download your results
Batch processing through the DQVerify Standalone Interface is self-serve and requires no SFTP configuration or sales cycle. Upload your CSV, select your process, and your processed file is automatically downloaded when complete. A manual download button is also available if you need to retrieve the file again. Data is processed on US servers — see our Privacy Policy for full details on data handling and residency.
Best practices
- Keep the original file until the processed file is validated.
- Use a unique identifier per record so you can match output rows back to input rows.
- Do not change expected column names without validating the new layout with DQVerify.
- Check rejected files and processing logs when a file fails to process.
- Review DQVerify output columns before updating production data.
Next steps
Understand DQE output columns
Every column DQVerify appends to your processed file, explained.
Postal Address Validation (RNVP) columns
Specific output fields produced by the postal address standardization service.
API Response Codes Reference
Complete reference for all HTTP and service-level response codes.