Pipeline runs CSV
textareaRequired input
Noderan MarketplaceData & Intelligence
Demo ReadyLive E2E verifiedDeterministic~10s
Pipeline Freshness Monitor
Profiles pipeline run rows against freshness SLAs and flags datasets running late. Returns structured, review-ready output without triggering any external action.
Profiles pipeline run rows against freshness SLAs and flags datasets running late.
Before you run
Workflow summary
Profiles pipeline run rows against freshness SLAs and flags datasets running late.
What is Pipeline Freshness Monitor?
Pipeline Freshness Monitor is a ready-to-run Noderan marketplace workflow for data & intelligence teams. It helps users move from a manual process to a repeatable automation with visible credit cost and app-based execution.
- Who is it for?
- Data platform teams
- What problem does it solve?
- Profiles pipeline run rows against freshness SLAs and flags datasets running late.
- How does it work?
- Profiles pipeline run rows against freshness SLAs and flags datasets running late.
- How does pricing work?
- 1 credit per run.
- What is the next action?
- Open the app marketplace to activate this workflow, or review credit pricing.
Pipeline Freshness Monitor FAQ
Short answers for activation, pricing, inputs, and execution review.
Profiles pipeline run rows against freshness SLAs and flags datasets running late. Returns structured, review-ready output without triggering any external action.
Expected inputs
Demo input
Csv
item,status,score orders 2h late,review,40 users on time,ready,95 revenue 6h late,review,25View raw JSON
{
"csv": "item,status,score\norders 2h late,review,40\nusers on time,ready,95\nrevenue 6h late,review,25"
}Output highlights
- rowCount
- columnCount
- headers
- findings
- previewRows
Example result
Row Count
3Column Count
3Headers
itemstatusscore
Findings
Pipeline rows include freshness SLA breaches for review.Parsed rows are ready for operator review
Preview Rows
1 structured item
View raw JSON
{
"rowCount": 3,
"columnCount": 3,
"headers": [
"item",
"status",
"score"
],
"findings": [
"Pipeline rows include freshness SLA breaches for review.",
"Parsed rows are ready for operator review"
],
"previewRows": [
{
"item": "Example",
"status": "review",
"score": "72"
}
]
}Use cases
- Know which datasets are stale before stakeholders do.
Step 1
Review the workflow and expected credit cost.
Step 2
Connect the tools or inputs required for execution.
Step 3
Run the workflow and inspect outputs in the app history.