My Hours to Looker Integration
AI-first ETL from My Hours into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads My Hours into Looker
Datrise syncs My Hours's time logs, projects, tasks, clients, team members, and billable rates into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.
Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.
Ideal for governed, version-controlled BI on a warehouse.
Endpoints
My Hours: Time tracking and billable hours for projects.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How My Hours entities map to Looker
| My Hours entity | Looker object | Notes |
|---|---|---|
| time logs | my_hours_time_logs | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| projects | my_hours_projects | id PK · linked to my_hours_time_logs |
| tasks | my_hours_tasks | id PK · linked to my_hours_time_logs |
| clients | my_hours_clients | id PK · linked to my_hours_time_logs |
FAQ
How does Datrise handle My Hours's custom fields in Looker?
Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.
How does the My Hours to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
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