Data validation platform
OdaChecker
A workspace for batch checks with task settings, a queue, statuses and result history.
- Role
- Architecture, interface and automation
- Project
- Data validation platform
- Year
- 2026
Task
Separate checks were hard to follow as one process. An operator needs to configure a task, launch it and understand what happens next. That requires a queue, clear status, errors and a way to return to results. The task was to bring these parts into an operations interface with access controls.
Solution
Built a Next.js interface and a Django REST API. Checks run through a Celery queue with Redis. Status and monitoring show execution progress, while results remain available in history. PostgreSQL stores the platform data. Access to workflows follows each user's permissions.
My contribution
- Designed the platform and developed the interface for configuring and launching checks.
- Implemented the API, task queue and status display with errors.
- Added result history, monitoring and access controls.
How it works
Configure
An operator configures a batch check.
Queue
Launches the task into the execution queue.
Monitor
Follows the execution status and any errors.
Review
Reviews the results and returns to them through history.
Stack
- Next.js
- Django REST
- PostgreSQL
- Celery
- Redis
Outcome
Each check has a complete path from configuration to a saved result. An operator can see the queue, task status and errors in one interface. History makes completed work available for later review.
Public version
The screenshot is anonymized. Validation rules, client data and internal infrastructure are intentionally withheld.
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