DatriseAI-first ETL

Microsoft Teams to Mode Integration

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

How Datrise loads Microsoft Teams into Mode

Datrise syncs Microsoft Teams's teams, channels, messages, users, meetings, and call records 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

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

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Microsoft Teams entities map to Mode

Microsoft Teams entityMode objectNotes
teamsmicrosoft_teams_teamsid PK · custom fields → flattened columns for SQL and notebooks
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 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 Microsoft Teams to Mode sync stay up to date?

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

Related pipelines

Early access

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