DatriseAI-first ETL

Microsoft Teams to Looker Studio Integration

AI-first ETL from Microsoft Teams into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Microsoft Teams into Looker Studio

Datrise syncs Microsoft Teams's teams, channels, messages, users, meetings, and call records into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Microsoft Teams: Team chat, channels, and meeting activity.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Microsoft Teams entities map to Looker Studio

Microsoft Teams entityLooker Studio objectNotes
teamsmicrosoft_teams_teamsid PK · custom fields → flattened columns for chart fields
channelsmicrosoft_teams_channelsid PK · linked to microsoft_teams_teams
messagesmicrosoft_teams_messagesid PK · linked to microsoft_teams_teams
usersmicrosoft_teams_usersid PK · linked to microsoft_teams_teams

FAQ

How does Datrise handle Microsoft Teams's custom fields in Looker Studio?

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

How does the Microsoft Teams to Looker Studio sync stay up to date?

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

Related pipelines

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