Granola integration

Granola data, in your warehouse.

A built-in ingestr connector: add credentials, pick tables, schedule it.

name: raw.notes
type: ingestr
parameters:
  source_connection: granola
  source_table: 'notes'
  destination: snowflake
  incremental_strategy: merge

$ bruin run assets/raw/granola.asset.yml

  1. extract · Granola notesincremental
  2. load · snowflake raw.notesmerged
  3. checks · not_null, unique

Loaded and checked. Downstream models can run.

How it connects

Connected in three steps.

Granola is an AI meeting-notes product.

  1. 01

    Add a Granola connection with its credentials.

  2. 02

    Pick the tables to load and how: replace, append or merge.

  3. 03

    Bruin runs it on your schedule and checks every load.

Tables

2 tables, ready to load.

  • notes
  • folders

The platform

Part of the Bruin platform.

Data in, ready for everything downstream: the models, the checks, the lineage and the AI layer.

01 · Move

Data Ingestion

02 · Model & govern

SQL & Python
Data Quality
Data Governance

03 · Use

AI Data Analyst
AI Dashboards
Data Apps
Self-Healing Pipelines
Bruin Cloudorchestration · governance · observability

Frequently asked

Questions about Granola.

Does Bruin have a built-in Granola integration?

Yes. Built-in ingestr source.

Which Granola tables can Bruin load?

notes, folders.

Where can Granola data go?

Snowflake, BigQuery, Databricks, Redshift, ClickHouse, Postgres, DuckDB, MotherDuck, Microsoft Fabric and more, plus files on S3 and GCS.

How fresh is the data?

As fresh as your schedule. Incremental loads append, merge or replace a time window, every few minutes if you like.

Do we need Bruin Cloud?

No. The Bruin CLI and ingestr run locally, in CI or in your own orchestrator. Bruin Cloud adds scheduling, lineage, alerts and the AI data analyst on top.

Ready to connect Granola?

$100 in credits and 50 AI tasks. No credit card.

A demo walks through your own data.

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