DatriseAI-first ETL

Megaplan GoodData

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

How Datrise loads Megaplan into GoodData

Datrise syncs Megaplan's contacts, accounts, deals, activities, and lifecycle events into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.

Ideal for embedded, multi-tenant analytics.

Endpoints

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

GoodData: Composable analytics platform with headless BI and embedded dashboards.

How Megaplan entities map to GoodData

Megaplan entityGoodData objectNotes
contactsmegaplan_contactsid PK · custom fields → flattened columns
accountsmegaplan_accountsid PK · linked to megaplan_contacts
dealsmegaplan_dealsid PK · linked to megaplan_contacts
activitiesmegaplan_activitiesdate dimensions events

FAQ

How does Datrise handle Megaplan's custom fields in GoodData?

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 GoodData types.

How does the Megaplan to GoodData sync stay up to date?

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

Related pipelines

Early access

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