Teradata to Looker Studio Integration

How Datrise loads Teradata into Looker Studio

Datrise syncs Teradata's tables, rows, schemas, indexes, primary indexes, and query history into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Teradata: Teradata analytical database for enterprise workloads.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Teradata entities map to Looker Studio

Teradata entity	Looker Studio object	Notes
tables	`teradata_d_tables`	id PK · custom fields → flattened columns for chart fields
rows	`teradata_d_rows`	id PK · linked to teradata_d_tables
schemas	`teradata_d_schemas`	id PK · linked to teradata_d_tables
indexes	`teradata_d_indexes`	id PK · linked to teradata_d_tables

FAQ

How does Datrise handle Teradata's custom fields in Looker Studio?

Flexible values are stored as flattened columns for chart fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker Studio types.

How does the Teradata to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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