Manatal to Tableau Integration
AI-first ETL from Manatal into Tableau. Governed entities, incremental sync, typed landing tables.
How Datrise loads Manatal into Tableau
Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.
Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.
Ideal for visual analytics and dashboards in Tableau.
Endpoints
Manatal: AI recruitment software with candidate scoring.
Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.
How Manatal entities map to Tableau
| Manatal entity | Tableau object | Notes |
|---|---|---|
| candidates | manatal_candidates | id PK · custom fields → flattened columns for Tableau fields |
| jobs | manatal_jobs | id PK · linked to manatal_candidates |
| applications | manatal_applications | id PK · linked to manatal_candidates |
| pipeline stages | manatal_pipeline_stages | id PK · linked to manatal_candidates |
FAQ
How does Datrise handle Manatal's custom fields in Tableau?
Flexible values are stored as flattened columns for Tableau fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Tableau types.
How does the Manatal to Tableau sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.
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