Day.ai → Holistics
AI-first ETL from Day.ai into Holistics. Governed entities, incremental sync, typed landing tables.
How Datrise loads Day.ai into Holistics
Datrise syncs Day.ai's contacts, accounts, deals, activities, and lifecycle events into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.
Ideal for as-code BI modeling on a warehouse.
Endpoints
Day.ai: AI-native CRM for relationship data, enrichment, and workflow automation.
Holistics: Self-service BI with modeling layers and scheduled report delivery.
How Day.ai entities map to Holistics
| Day.ai entity | Holistics object | Notes |
|---|---|---|
| contacts | day_ai_contacts | id PK · custom fields → flattened columns for the modeling layer |
| accounts | day_ai_accounts | id PK · linked to day_ai_contacts |
| deals | day_ai_deals | id PK · linked to day_ai_contacts |
| activities | day_ai_activities | date/time dimensions events |
FAQ
How does Datrise handle Day.ai's custom fields in Holistics?
Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.
How does the Day.ai to Holistics sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the modeled tables.
Related pipelines
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