DatriseAI-first ETL

Megaplan Qlik

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

How Datrise loads Megaplan into Qlik

Datrise syncs Megaplan's contacts, accounts, deals, activities, and lifecycle events 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

Megaplan: CRM with strong adoption in CIS markets for sales and operations.

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

How Megaplan entities map to Qlik

Megaplan entityQlik objectNotes
contactsmegaplan_contactsid PK · custom fields → flattened columns for the data model
accountsmegaplan_accountsid PK · linked to megaplan_contacts
dealsmegaplan_dealsid PK · linked to megaplan_contacts
activitiesmegaplan_activitiesdate/time fields events

FAQ

How does Datrise handle Megaplan'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 Megaplan 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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