DatriseAI-first ETL

Clay to Qlik Integration

AI-first ETL from Clay into Qlik. Governed entities, incremental sync, typed landing tables.

How Datrise loads Clay into Qlik

Datrise syncs Clay's tables, rows, enrichment runs, waterfalls, data sources, and exported lists into Qlik as tables loaded into Qlik's associative engine (often via QVD). Flexible or custom fields land in flattened columns for the data model, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental QVD loads merged on stable id, so re-runs update only what changed. QVD files per entity and load date. Qlik's associative model joins on identically named fields, so Datrise standardizes key names so associations link correctly.

Ideal for associative, in-memory exploration in Qlik Sense.

Endpoints

Clay: Data enrichment tables that build outbound lists.

Qlik: Associative analytics with Qlik Sense apps and governed data models.

How Clay entities map to Qlik

Clay entityQlik objectNotes
tablesclay_tablesid PK · custom fields → flattened columns for the data model
rowsclay_rowsid PK · linked to clay_tables
enrichment runsclay_enrichment_runsid PK · linked to clay_tables
waterfallsclay_waterfallsid PK · linked to clay_tables

FAQ

How does Datrise handle Clay's custom fields in Qlik?

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

How does the Clay to Qlik sync stay up to date?

It runs incrementally — Datrise uses incremental QVD loads merged on stable id.

Related pipelines

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