Clay to Tableau Integration

How Datrise loads Clay into Tableau

Datrise syncs Clay's tables, rows, enrichment runs, waterfalls, data sources, and exported lists 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

Clay: Data enrichment tables that build outbound lists.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Clay entities map to Tableau

Clay entity	Tableau object	Notes
tables	`clay_tables`	id PK · custom fields → flattened columns for Tableau fields
rows	`clay_rows`	id PK · linked to clay_tables
enrichment runs	`clay_enrichment_runs`	id PK · linked to clay_tables
waterfalls	`clay_waterfalls`	id PK · linked to clay_tables

FAQ

How does Datrise handle Clay'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 Clay to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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