DatriseAI-first ETL

Yandex Metrica Yellowfin

AI-first ETL from Yandex Metrica into Yellowfin. Governed entities, incremental sync, typed landing tables.

How Datrise loads Yandex Metrica into Yellowfin

Datrise syncs Yandex Metrica's records, events, and configuration objects into Yellowfin as warehouse tables Yellowfin builds views on. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.

Ideal for dashboards with automated data storytelling.

Endpoints

Yandex Metrica: SaaS or API data source for analytics and warehouse sync.

Yellowfin: BI suite with dashboards, automated insights, and data storytelling.

How Yandex Metrica entities map to Yellowfin

Yandex Metrica entityYellowfin objectNotes
recordsyandex_metrica_recordsid PK · custom fields → flattened columns
eventsyandex_metrica_eventsdate/time dimensions events
configuration objectsyandex_metrica_configuration_objectsid PK · linked to yandex_metrica_records

FAQ

How does Datrise handle Yandex Metrica's custom fields in Yellowfin?

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

How does the Yandex Metrica to Yellowfin sync stay up to date?

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

Related pipelines

Early access

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