From Solution to Community Tool
A few weeks ago, I shared how CSVValidationApp helps solve data quality issues in SAP SuccessFactors Talent Intelligence Hub. The response surprised me. Many have built similar workarounds, spent hours cleaning data manually, or watched perfectly good imports fail because of stray HTML tags.
That's when I felt this shouldn't be “my tool.” It should be our tool.
Today, CSV Validator App is officially open source and available on GitHub under the Apache 2.0 license: github.com/SAP/csv-validator
Why This Matters
I didn't build this tool because I love CSV files (I don't). I built it because I was tired of seeing good work derailed by preventable issues. An HR team prepares a skills library update, exports clean data, imports it into TIH—and suddenly descriptions are broken, special characters are corrupted, and they're troubleshooting instead of enabling their workforce.
It's frustrating. And it's common.
Making this open source isn't about recognition or downloads. It's about honesty: I don't have all the answers. You might be importing recruiting data with different quirks. You might support a region with specific character encoding needs. You might have found a validation rule I missed.
By opening the code, we can solve these problems together—transparently, collaboratively, and faster than any of us could alone.
What You're Getting
This is a complete SAP Fiori application you can run today:
Core Validation:
- Detects encoding issues (UTF-8 compliance, BOM, null bytes)
- Validates CSV structure (headers, delimiters, column consistency)
- Identifies problematic content (HTML tags, entities, control characters, special characters)
- Checks field lengths and data integrity
Auto-Correction:
- Strips HTML tags while preserving content
- Converts HTML entities to UTF-8 characters (
ü→ ü) - Properly escapes special characters
- Generates a clean, download-ready corrected file
UI Features:
- Drag-and-drop file upload
- Interactive preview of your CSV
- Filterable table showing issues by row and type
- Side-by-side view of original vs. corrected content
- One-click download of the corrected file
Privacy:
- Everything runs locally in your browser
- No uploads, no servers, no data leaves your machine
It's built with SAP UI5, follows SAP Fiori standards, and runs via npm. Five minutes from clone to validation.
Getting Started
git clone https://github.com/SAP/csv-validator.git
cd csv-validator
npm install
npm startOpen your browser to the app url, drop in a CSV file, and click Validate. That's it.
You can test by uploading your csv and press validate. Here is a sample screenshot of what you can expect:
Where We Go From Here
I have ideas for improvements—support for other SuccessFactors modules, batch processing, direct API integration. But I'm more interested in hearing yours.
If you use this tool and it helps, tell me what's missing. If it doesn't catch an issue it should, open a GitHub issue with an example. If you have a fix or enhancement, submit a pull request. If you just want to share your experience, leave a comment below.
This isn't a finished product. It's a starting point. I'm learning as much from your use cases as you might learn from the code.
An Honest Ask
If you work with SuccessFactors data imports—whether you're an administrator, consultant, or developer—try this tool with your real files. Not a sanitized demo file. Your actual data (with sensitive info removed, of course).
Then tell me:
- Did it catch issues you would have missed?
- Did it flag false positives that aren't actually problems?
- What validation rule would make your life easier?
And if you've built something similar or have ideas for collaboration, let's talk. The goal isn't to centralize everything into this one tool—it's to raise the baseline for data quality across the community.
Resources:
Data quality shouldn't be a bottleneck. Let's make it a strength—together.
