Google BigQuery to Klipfolio Integration

How Datrise loads Google BigQuery into Klipfolio

Datrise syncs Google BigQuery's datasets, tables, views, query jobs, table schemas, and partitions into Klipfolio as query-ready tables or feeds Klipfolio reads. Flexible or custom fields land in flattened columns for Klips, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or data feeds, so re-runs update only what changed. Date-partitioned facts for trend Klips. Klipfolio pulls from sources on a refresh interval, so Datrise keeps tables incrementally current to match.

Ideal for real-time KPI dashboards and wallboards.

Endpoints

Google BigQuery: Serverless analytics warehouse on Google Cloud.

Klipfolio: Dashboard platform for real-time KPIs and metric wallboards.

How Google BigQuery entities map to Klipfolio

Google BigQuery entity	Klipfolio object	Notes
datasets	`bigquery_datasets`	id PK · custom fields → flattened columns for Klips
tables	`bigquery_tables`	id PK · linked to bigquery_datasets
views	`bigquery_views`	id PK · linked to bigquery_datasets
query jobs	`bigquery_query_jobs`	id PK · linked to bigquery_datasets

FAQ

How does Datrise handle Google BigQuery's custom fields in Klipfolio?

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

How does the Google BigQuery to Klipfolio sync stay up to date?

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

Related pipelines

Early access

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