Datost Documentation archiveCurrent E1O project ↗
Historical documentation · May 7, 2026

This snapshot describes Datost’s former Slack-native analytics product. It is retained for reference; setup instructions, service availability and external links may have changed. It does not describe E1O glasses.

BigQuery

Connect your Google BigQuery project to Datost and query it from Slack or the web app.

Once connected, anyone on your team can ask Datost questions in plain English and have them answered against live data in your BigQuery datasets.

What you get

  • Ask questions like @Datost what was MRR last week by plan? in Slack and have the answer pulled straight from BigQuery.
  • Automatic table and column discovery across every dataset your credentials can see.
  • Support for views, nested STRUCT/RECORD columns, and standard SQL types.

Prerequisites

Before connecting, make sure you have:

  • A Google Cloud project with the BigQuery API enabled.
  • BigQuery Data Viewer and BigQuery Job User roles on the datasets you want Datost to read. BigQuery Metadata Viewer also works if you only want schema discovery.
  • Permission to read INFORMATION_SCHEMA on each dataset you want available for questions.

Authentication methods

Datost supports two ways to authenticate to BigQuery. Pick the one that fits your setup.

Sign in with Google (OAuth)

Best for getting started quickly. Datost uses the signed-in user's permissions, so the connection can only see what that user can see.

Service account key

Best for production and shared org-wide access. Create a service account in GCP, grant it the roles above on the datasets you want Datost to query, and upload the JSON key when connecting.

Connect BigQuery

Open the admin panel

In the Datost web app, go to Data Sources and click Add data source.

Pick BigQuery

Select BigQuery from the list of warehouse types.

Choose an auth method

Toggle between Sign in with Google and Service Account at the top of the form.

Authenticate

  • OAuth: click Sign in with Google, approve the bigquery.readonly scope in the popup, then pick a GCP Project ID from the dropdown.
  • Service account: paste the full JSON key into the Service Account Key field. Datost will extract the project ID automatically.

Set a default dataset (optional)

Fill Default Dataset to let Datost resolve unqualified table names. You can leave it blank if your questions always reference dataset.table.

Test and save

Click Test Connection. Datost lists the datasets the credentials can see as a sanity check. If it passes, name the connection and save.

How querying works

Datost queries BigQuery live for every question. Nothing from your tables is copied into Datost storage.

  • Rows are capped at 1,000 per query to keep responses fast, and results are truncated past that limit.
  • Every BigQuery job is tagged with a source: datost label so you can filter them in GCP billing and audit logs.
  • Only metadata (table and column names) is cached briefly to speed up follow-up questions.

Permissions and limits

  • BigQuery does not expose primary or foreign keys, so Datost infers relationships from column names and context.
  • Datasets without INFORMATION_SCHEMA read access are silently skipped during table discovery.
  • OAuth access tokens are refreshed automatically; refresh tokens are encrypted per-organization at rest.