UiPath Documentation
industry-department-solutions
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  • Overview
    • Introduction
    • Getting Started
    • Integration walkthrough
    • API Guide
    • Schema lifecycle
    • Scheduled ingestion
    • Historical data ingestion
    • Data Quality Dashboard
    • Customizations
    • Data Onboarding Checklist
  • API Resources

Supply Chain & Retail Solutions API guide

Data Quality Dashboard

The Data Quality Dashboard is a pre-built canvas asset that lets you monitor your tenant's ingestion runs end-to-end. Once a solution is rolled out and starts ingesting, the dashboard surfaces:

  • How many records have been processed
  • How many rows passed or failed validation
  • Which tables and which solutions are affected
  • Which error codes are most frequent
  • The exact failed rows, with the source field values that caused validation to fail

Data flows in automatically — nothing additional is needed at ingest time. Every validated row contributes to the dashboard, regardless of how it was ingested (see API Guide — Validation behavior).

Prerequisites

Before you start, make sure:

  • Your tenant is on the latest ingestion release. The dashboard depends on the validation feature that ships in this release. If your tenant has not been upgraded yet, submit a support ticket.
  • At least one solution has been rolled out in the tenant via the ingestion API (see Schema lifecycle). The dashboard renders empty until a rollout has happened.
  • You have permission to create canvas assets.

Setting up the dashboard (one-time)

Setup is a one-time task per tenant, performed by a tenant admin. Three steps.

Step 1 — Register the Data Quality Dashboard action

The dashboard reads aggregated validation metrics through a backend action that needs to be registered in your tenant before the dashboard widgets can fetch data.

  1. Go to Actions in the tenant settings.
  2. Select Add new action and choose the API spec / OpenAPI option.
  3. Paste the OpenAPI spec for the dashboard. The current spec is provided by Peak when you request dashboard setup — submit a support ticket if you do not have it.
  4. Save the action with the exact name Data Quality Dashboard APIs.

Step 2 — Open canvas and select the namespace

  1. Open Canvas in the tenant.
  2. When prompted to choose a metrics namespace, pick peak__dq_dashboard.

This namespace is reserved for Peak-managed dashboards — the dashboard's KPI cards and detail tables read their numbers from cubes published into it whenever a solution is rolled out, upgraded, or has a column added.

Warning:

Do not publish your own cubes into peak__dq_dashboard. Pick a different namespace for any custom dashboard work.

Step 3 — Create the asset from the template

  1. With the namespace selected, open the Templates library in canvas.
  2. Find the template named Data Quality Dashboard and select it — a preview of the layout is shown.
  3. Select Create asset, give it a name (for example, Data Quality Dashboard), and confirm.

The asset is now yours: rename it, share it, embed it in spaces, or duplicate it. Edits you make to your asset do not affect other tenants' copies.

What's in the dashboard

The dashboard is a single scrolling overview page, plus a table-level detail view you reach by drilling into any table. Every panel on the overview responds to the filters at the top.

Monitoring filters

A filter bar scopes every panel on the page:

  • Start date and End date — set the monitoring window. All KPIs, charts, and tables are calculated for this window.
  • Solution — focus on a single solution, or leave it on All solutions to span the whole tenant.

Period-over-period comparisons on the KPI cards are measured against the immediately preceding window of equal length — for example, a 93-day window is compared with the previous 93 days.

Current health snapshot

Five KPI cards summarize the selected window. Each card shows the headline number plus how it has moved versus the previous, equal-length window:

  • Total requests — number of ingestion requests received.
  • Rows processed — total rows seen across those requests.
  • Validation failures — rows that failed validation.
  • Rows ingested — rows that passed validation and were written to the destination.
  • Pass rate — share of processed rows that passed validation.

Charts

Three time-series charts plot trends across the selected window:

  • Error-code trend — daily stacked failed-row counts for the top six error-code series, with all remaining series grouped into Other. Shows which error codes are driving failures, and when.
  • Validation results over time — daily failed and successful row counts side by side.
  • Pass rate over time — pass rate on a fixed 0–100% scale, so quality is comparable across windows.

Tables

  • Top error codes — error codes ranked by total occurrences in the window, each with a plain-language description (for example, DI_E_22023Value is not one of the allowed enum values). Use it to find the most common data-quality issues to fix at the source.
  • Breakdown by table — one row per table, with its solution, run count, and failed / success / total row counts. The list is searchable and sortable, and paginated. Select a table name to open its detail view, scoped to the active solution and date range.
  • Breakdown by request — a collapsible secondary view, sorted by failed rows highest first, for investigating a specific ingestion request. Select Show requests to expand it.

Current slice summary

A short narrative of the selected window — overall pass rate, the table with the most failures, and the top error code — followed by a Coverage line stating how many tables across how many solutions were monitored in the window.

Table detail

Selecting a table name in Breakdown by table opens a detail view scoped to that table, solution, and date range. It lists the failed rows for the table, including the source field values that caused validation to fail, so you can reproduce and fix them. Hover any error code to see what it means.

What you can monitor

At a glance:

MetricWhere to find itUse it to…
Rows processed, rows ingested, pass rateCurrent health snapshot KPI cardsTrack ingestion health over the selected window
Failed vs successful rows over timeValidation results over time / Pass rate over time chartsSpot regressions after a release or schema change
Error codes over timeError-code trend chartSee which error codes drive failures, and when
Top error codesTop error codes tableIdentify the most common data-quality issues to fix at the source
Per-table breakdownBreakdown by tableFind which tables are contributing most failures
Per-request breakdownBreakdown by requestInvestigate a specific ingestion request
Per-solution breakdownSolution filterCompare quality across multiple solutions in the same tenant
Failed rows with source valuesTable detail viewReproduce and fix the rows that did not pass validation

When data appears

Ingestion runs on a schedule — once every 30 minutes by default — so data is not instant. Your first request may take roughly 30–50 minutes to appear, depending on how close it lands to the next scheduled run. As soon as that ingestion completes, the Data Quality Dashboard is updated.

The 30-minute interval can be changed for your tenant — submit a support ticket to adjust it.

Once a solution is rolled out and ingestion has run, records start showing up. The underlying metrics cube refreshes every few minutes, so very recent activity may take a moment to appear after each run.

Common questions

Why is one of my solutions missing from the solution filter?

The filter lists solutions that have at least one validation record. Freshly-rolled-out solutions with zero ingestions will not appear until their first request runs through validation.

Why is the breakdown-by-table widget empty?

Either no validation records have landed in the selected date range, or your selected solution filter is excluding everything. Try widening the date range or clearing the solution filter.

Why don't I see source columns in the table detail view?

Source columns are only carried for tables that came from the supported standard schemas. Custom tables and custom-added columns appear in the dashboard's audit columns only.

Can I customize the dashboard?

Yes. The asset created from the template is a normal canvas asset — you can edit widgets, add pages, change the styling, and so on. Re-creating the asset from the template will overwrite your edits, so save a copy first if you want to keep them.

Who do I contact for issues?

Submit a support ticket with: your tenant name, the asset ID (visible in the canvas URL), and a screenshot of what you're seeing. Include the time range you were looking at — it speeds up the triage significantly.

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