DatriseAI-first ETL

Everhour to ThoughtSpot Integration

AI-first ETL from Everhour into ThoughtSpot. Governed entities, incremental sync, typed landing tables.

How Datrise loads Everhour into ThoughtSpot

Datrise syncs Everhour's time entries, projects, tasks, users, clients, and budgets into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

Everhour: Time tracking and budgets for project teams.

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Everhour entities map to ThoughtSpot

Everhour entityThoughtSpot objectNotes
time entrieseverhour_time_entriesid PK · custom fields → flattened columns for searchable fields
projectseverhour_projectsid PK · linked to everhour_time_entries
taskseverhour_tasksid PK · linked to everhour_time_entries
userseverhour_usersid PK · linked to everhour_time_entries

FAQ

How does Datrise handle Everhour's custom fields in ThoughtSpot?

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

How does the Everhour to ThoughtSpot sync stay up to date?

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

Related pipelines

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