I'm building a dashboard and need a dataset API with scheduled updates

Sure — I can help design that.

A dataset API with scheduled updates usually has two parts:

1. API layer

   • Exposes dataset endpoints for your dashboard
   • Supports filtering, pagination, and versioning
   • Returns data in JSON, CSV, or both

2. Scheduled refresh layer

   • Pulls from source systems on a cron schedule
   • Rebuilds or increments the dataset
   • Optionally stores snapshots for historical reporting

Typical architecture

• Source connectors: databases, files, third-party APIs
• Job scheduler: cron, Celery beat, Airflow, GitHub Actions, or a cloud scheduler
• Processing pipeline: validate, transform, deduplicate, aggregate
• Storage: Postgres, BigQuery, S3, or a data warehouse
• Dataset API: FastAPI / Flask / Node / serverless endpoints

Common API endpoints

• GET /datasets — list available datasets
• GET /datasets/{id} — get metadata
• GET /datasets/{id}/records — fetch records
• GET /datasets/{id}/refresh — trigger refresh manually
• GET /datasets/{id}/status — last update time, refresh state, row count

Scheduled update patterns

• Full refresh: replace dataset every run
• Incremental refresh: update only changed records
• Snapshot refresh: keep time-based versions for analytics

Important features for a dashboard

• Caching for fast reads
• API keys / auth
• Rate limiting
• Audit logs
• Last-updated timestamps
• Failure alerts when a scheduled job breaks

Example schedule

• Every 15 minutes for operational dashboards
• Hourly for business dashboards
• Daily for reporting dashboards

If you want, I can help you with one of these next:

1. a system design for this API,
2. a FastAPI implementation example,
3. a database schema for scheduled dataset refreshes,
4. or a cloud deployment plan.