/uipath-process-mining

name: uipath-process-mining
description: "UiPath Process Mining via `uip pm` — build and operate a process app end-to-end from a CSV / event log: templates, data mapping, upload, ingest, the dbt (Snowflake) transformation layer, publish, and query it (metrics, percentiles, RCA). Covers `uipath.custom`, the `Cases.sql` optional-column gotcha, Case-linked data-model tables (add-table + re-ingest), the apply-not-reingest fix loop, fixing a wrong mapping in place via `apps data-mapping get|update` (no app rebuild), and editing the app model via `apps model fields` — a field's data kind / calculated fields, including the numeric→duration mismatch that locks dashboards open. For Orchestrator/Data Fabric/Integration Service→uipath-platform. For `.flow`/Maestro→uipath-maestro-flow. For IXP→uipath-ixp."
when_to_use: "User mentions process mining, a process app, an event log, `uip pm`, mining a CSV/log, ingesting data into one, dbt/SQL transformations, steps-to-resolution / throughput / variant / rework analysis, or querying one. Also 'build a process app from this data', 'ingest this log', 'fix my Cases.sql', 'why can't I query my custom table', 'add a table to the data model', 'group by X average Y', 'fix/change/read my data mapping', 'wrong date format in the mapping', 'change a field's data kind', 'set a field to duration', 'add a calculated field/metric', 'my dashboards won't open', 'Must be duration not numeric'. For Orchestrator/Data Fabric→uipath-platform; `.flow`→uipath-maestro-flow; IXP→uipath-ixp."
allowed-tools: Bash, Read, Write, Glob, Grep

UiPath Process Mining — `uip pm` Assistant

Build and operate a UiPath Process Mining process app end-to-end from the terminal with `uip pm`: from a raw CSV to a queryable process model. The whole loop — templates, data mapping, upload, ingest, the dbt/Snowflake transformation layer, and querying — is scriptable; **use the CLI, don't hand-roll the Process Mining REST API.**

**This works for every app type**, not just `uipath.custom`: the pipeline (mapping → upload → ingest → transform → data model → query) is identical across the `uipath.custom` event-log template and the source-system templates (P2P / O2C / IM / AP / … on SAP, Oracle, NetSuite, ServiceNow, Salesforce, …). Only **what the data mapping / extract must contain** differs. See [`references/app-types.md`](references/app-types.md).

This skill is the **process-mining domain layer** — *what* to build and *why*. The low-level mechanics of driving the tool — the command-group map, the `Result`/`Code`/`Data` output envelope, the ETag get-modify-put pattern, `--wait`, `--stage`, and field-id discovery — are one layer down in [`references/uip-pm-cli.md`](references/uip-pm-cli.md). The rules below carry the headline command and link down to it and to the domain references for the full detail.

When to Use This Skill

• **Build a process app from data** — you have a CSV / event log and want a mined process (throughput, variants, rework, steps-to-resolution).
• **Author the transformation layer** — edit the dbt (Snowflake) SQL models that produce the process model, then re-run.
• **Query a process app** — pull numbers out: aggregate group-by + metrics, raw detail rows, percentiles, root-cause analysis, process insights.
• **Expose custom analysis** — surface your own analytical table (a weekly aggregate, an impact study) as a queryable entity.
• **Edit the app model** — change a field's data kind, add calculated fields, or fix a data-kind mismatch that locks dashboards open.
• **Manage the app lifecycle** — stages (dev → published), RBAC, deletion.

App lifecycle

An app moves through: **create** (from a template + data mapping) → **load** (upload + ingest) → **transform** on the **dev** stage (the ELT/dbt layer) → **publish** to the **published** stage → **query** / build dashboards. Develop against a small subset on `dev`, then publish the full dataset for real analysis ([`references/lifecycle-and-rbac.md`](references/lifecycle-and-rbac.md)). The **ELT editor** is the `transformations` command group over the dbt (Snowflake) model tree that turns loaded source tables into the process model — its command surface and the apply-vs-run distinction are in [`references/transformations.md`](references/transformations.md).

Critical Rules

1. **To make a custom analytical table queryable, register it as a Case-linked data-model table, then RE-INGEST.** Process Mining is **case-centric**: a queryable table must be the `Cases` root or reach `Cases` via a foreign key — an unlinked table is rejected at query time (`UserError_TableIsDeleted`). First check the built-in Case-child slots: **`Tags`** (multi-valued per-case labels: `Tag`/`Tag_type`) and **`Due_dates`** (per-case SLA/deadline: `Expected_date`/`Actual_date`/`On_time`/`Cost`) — populate their dbt models rather than adding a table when your data fits. Otherwise register a custom table with **`uip pm apps data-model add-table <app> --file <table.json>`**, where the file is a DataModelDto entry `{ name, primaryKey, foreignKeys:[{table:"Cases",column:"Case_ID"}] }` (loose-link a standalone aggregate with a surrogate PK + nullable `Case_ID`). `add-table` edits `/dev/dataModel` (upsert, ETag-safe) then `applyCurrentDatamodel`; the table only becomes queryable after **`ingestions create --wait`** (a data-model edit takes effect only on the next ingestion). Full recipe + Tags/Due_dates decision table in [`references/data-model.md`](references/data-model.md).

2. **Match the template to the data — the rest of the pipeline is identical for all app types.** A single denormalized log (Case, Activity, Timestamp [+ attributes]) ⇒ `uipath.custom` ("Event log"). Otherwise pick the `<process>.<system>` template matching your source system AND process (Purchase-to-Pay on SAP ⇒ `uipath.p2p.sap`; incidents from ServiceNow ⇒ `uipath.im.servicenow`) — but only when you actually have that system's **full multi-table extract**, not a single log you expo