DatriseAI-first ETL

Harvest Qlik

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

How Datrise loads Harvest into Qlik

Datrise syncs Harvest's time entries, projects, clients, invoices, and utilization 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

Harvest: Time tracking and project profitability for services teams.

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

How Harvest entities map to Qlik

Harvest entityQlik objectNotes
time entriesharvest_time_entriesid PK · custom fields → flattened columns for the data model
projectsharvest_projectsid PK · linked to harvest_time_entries
clientsharvest_clientsid PK · linked to harvest_time_entries
invoicesharvest_invoicesid PK · linked to harvest_time_entries

FAQ

How does Datrise handle Harvest'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 Harvest 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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