DatriseAI-first ETL

Snapchat Marketing Mode

AI-first ETL from Snapchat Marketing into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Snapchat Marketing into Mode

Datrise syncs Snapchat Marketing's records, events, and configuration objects into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

Snapchat Marketing: SaaS or API data source for analytics and warehouse sync.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Snapchat Marketing entities map to Mode

Snapchat Marketing entityMode objectNotes
recordssnapchat_marketing_recordsid PK · custom fields → flattened columns for SQL and notebooks
eventssnapchat_marketing_eventstemporal columns events
configuration objectssnapchat_marketing_configuration_objectsid PK · linked to snapchat_marketing_records

FAQ

How does Datrise handle Snapchat Marketing's custom fields in Mode?

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

How does the Snapchat Marketing to Mode sync stay up to date?

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

Related pipelines

Early access

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