Data Schedules
Carbon Arc’s data pipelines run on defined refresh schedules to give users greater visibility into data readiness and reliability. This helps you make smarter, better-timed decisions when purchasing new increments of streaming or panel-based datasets.
Understanding when a dataset was last updated—and when it’s expected to update again—lets you better align usage with business needs, ensuring fresher insights and minimizing lags in analysis.
Where to Access Refresh Details
You can view the current schedule within the Data Library, all times are in Eastern Standard Time (EST). In the near future, we’ll roll out dynamic access to refresh metadata directly within the Platform UX and Python SDK, allowing for near real-time visibility across your workflows. , all times are in Eastern Standard Time (EST). In the near future, we’ll roll out dynamic access to refresh metadata directly within the Python SDK, allowing for near real-time visibility across your workflows.
Key Fields in the Schedule
| Field | Description |
|---|---|
| Last Refresh Date | Timestamp of the most recent successful dataset update |
| Next Refresh Date | Projected date of the next update, subject to vendor timelines or operational shifts |
Why This Matters
Refresh metadata gives you an at-a-glance read on pipeline health and data currency—especially important when aligning insights with reporting cycles, trading models, or other uses. It also lets you identify when to hold off on purchases or expect the next release of an increment.
FAQs
How often are datasets updated?
Update frequency varies by dataset. Refer to the “Next Refresh” and “Average Run Duration” fields for expected cadence.
What happens if a dataset is delayed?
If a refresh is delayed, the “Next Refresh Date” will adjust accordingly based on real-time pipeline status.
Contact us at support@carbonarc.co if you have any questions!