DatriseAI-first ETL

1С:CRM Sisense

AI-first ETL from 1С:CRM into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads 1С:CRM into Sisense

Datrise syncs 1С:CRM's contacts, accounts, deals, activities, and lifecycle events into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.

Ideal for embedded analytics on an in-memory engine.

Endpoints

1С:CRM: CRM with strong adoption in CIS markets for sales and operations.

Sisense: Analytics platform with elastic data models and embedded analytics.

How 1С:CRM entities map to Sisense

1С:CRM entitySisense objectNotes
contacts1c_crm_contactsid PK · custom fields → flattened columns for the cube
accounts1c_crm_accountsid PK · linked to 1c_crm_contacts
deals1c_crm_dealsid PK · linked to 1c_crm_contacts
activities1c_crm_activitiesdate/time fields events

FAQ

How does Datrise handle 1С:CRM's custom fields in Sisense?

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

How does the 1С:CRM to Sisense sync stay up to date?

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

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