What problem does it solve? Turning a raw CSV or event log into a queryable UiPath Process Mining app involves many failure-prone steps — data mapping, ingestion, dbt/Snowflake transformations, data-model registration, and publishing — and this Skill guides the entire loop through the uip pm CLI while preventing the common pitfalls (Cases.sql optional-column errors, wrong mappings, unqueryable custom tables, and the DNA-46960 dashboard lockout). ## Core Features & Use Cases - End-to-end app pipeline: discover templates, create an app from a data mapping, upload files, ingest, patch the dbt transformation layer, publish, and query with group-by/metric sugar. - Fix-in-place recovery: repair a wrong data mapping via apps data-mapping get|update without recreating the app, and re-run failed transforms with transformations apply instead of re-ingesting. - Custom analytics: register custom dbt models as Case-linked data-model tables so they become queryable, and edit field data kinds or calculated fields via apps model fields. - Use Case: You have a service-desk CSV export and want throughput and variant analysis — the Skill walks you from pre-flight file checks through a working process app you can query with query run --group-by ... --metric .... ## Quick Start Ask the assistant to build a UiPath Process Mining app from your CSV event log using the uip pm CLI, starting with template discovery and a minimal data mapping.
