BambooHR → Mode
AI-first ETL from BambooHR into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads BambooHR into Mode
Datrise syncs BambooHR's employee records, org structure, lifecycle events, and workforce attributes into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
BambooHR: HRIS source for employee records and workforce analytics.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How BambooHR entities map to Mode
| BambooHR entity | Mode object | Notes |
|---|---|---|
| employee records | bamboohr_employee_records | id PK · custom fields → flattened columns for SQL and notebooks |
| org structure | bamboohr_org_structure | id PK · linked to bamboohr_employee_records |
| lifecycle events | bamboohr_lifecycle_events | temporal columns events |
| workforce attributes | bamboohr_workforce_attributes | id PK · linked to bamboohr_employee_records |
FAQ
How does Datrise handle BambooHR's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the BambooHR to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for BambooHR
Early access
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