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Documentation Index

Fetch the complete documentation index at: https://docs.summation.com/llms.txt

Use this file to discover all available pages before exploring further.

The Connectors page is where you set up the data sources Summation can read from. Once a connection is configured, you pick which tables, files, or repositories to bring in as datasets — and those datasets become available everywhere else in the product: Addison, reports, dashboards, and the modeler.

Terminology

Three terms get used throughout this section. They’re easy to mix up:
TermWhat it isExample
ConnectorA type of integration.Snowflake, Postgres
ConnectionA specific instance of a connector with credentials filled in.Acme Corp’s prod warehouse
DatasetOne source object (table, view, file, or repo) pulled in through a connection.analytics.public.orders
You can have multiple connections of the same connector type — for example one Snowflake connection for production and another for staging.
Screenshot needed: Connectors list page (/connectors) showing the table of existing connections — type badge, name, description, last-updated date, and status indicator.

Supported connectors

Snowflake

Cloud data warehouse

BigQuery

Google Cloud data warehouse

Databricks

SQL Warehouse, Spark Connect, or Delta Lake

Postgres

PostgreSQL and compatible databases

MySQL

MySQL and compatible databases

ClickHouse

Columnar OLAP database

Oracle

Oracle Database, including Autonomous DB

MotherDuck

Hosted DuckDB

S3

AWS object storage (Parquet, CSV, JSON)

GitHub

Code repositories and issues
Don’t see what you need? Tell us — connectors are added regularly.

Adding a connection

Connections are created through a three-step wizard. Click New connection on the Connectors page to start.
1

Choose a data source

Pick a connector type from the grid. Snowflake, Postgres, and BigQuery are surfaced first as the most commonly used.
Screenshot needed: Step 1 of the wizard — “Choose a data source” with the connector type grid.
2

Enter connection details

Give the connection a name and an optional description, then fill in the connector-specific fields.
  • Name — used as an identifier in SQL and APIs. Must start with a letter and only contain letters, numbers, hyphens, and underscores.
  • Description — free text to help teammates recognize the connection.
  • Credentials and configuration — vary by connector. See the per-connector pages below for what each field means and where to find the values.
Click Test connection before continuing. A green check means Summation could authenticate and reach your data; a red error includes the message returned by the source.
Screenshot needed: Step 2 of the wizard — “Connection details” with name, description, connector-specific fields, and the Test connection button.
3

Add datasets

Pick the tables, files, or repositories Summation should expose. The wizard shows a browser tailored to the connector — a database/schema/table tree for warehouses, a file browser for S3, a repo picker for GitHub.Each selection becomes a dataset. Dataset names must be unique across your tenant; the wizard suggests a unique name automatically when there’s a conflict.
Screenshot needed: Step 3 of the wizard — “Add datasets” showing the source browser on the left and the staged dataset list on the right.

Per-connector setup guides

Each guide documents the exact fields shown in that connector’s form.

Managing a connection

Click any row on the Connectors page to open its detail view. From there you can:
  • View configuration — see the non-secret fields (host, account, database, etc.) and which secrets are stored. Secret values themselves are never shown after save.
  • Edit settings — update credentials when they rotate, or change configuration like the warehouse, role, or region.
  • Add datasets — bring in additional tables, files, or repositories.
  • Re-sync — refresh schema and metadata for selected datasets.
  • Disconnect — disconnect every dataset in this connection at once. Datasets from other connections aren’t affected. Reconnect later from the same page.
  • Delete — permanently remove the connection, its credentials, and all of its datasets.
Screenshot needed: Connector detail page showing the Settings panel and the Datasets table side-by-side, with the Disconnect / Delete actions visible.

Connection statuses

The colored dot on each connection shows its current state:
StatusColorWhat it means
ActiveGreenThe connection is healthy and its datasets are queryable.
ProcessingYellowDatasets are deploying or syncing in the background.
ErrorRedThe last operation failed. Open the connection to see what went wrong.
DisconnectedGreyThe connection is paused. Datasets stay defined but no queries will run until you reconnect.

File uploads

Summation also accepts CSV and Excel files directly — no connector required.
  • Files uploaded inside a project (via the project’s Import menu) are local to that project.
  • Files uploaded through the Connectors page are tenant-wide and behave like any other dataset.
Uploaded files are parsed and previewed before import — you can review the inferred columns and types, and rename columns, before committing.
For larger files, or anything that updates regularly, prefer a real connector over re-uploading. CSVs are great for one-off analyses; warehouses are better for anything you’ll come back to.

Permissions

Creating, editing, and deleting connections requires admin permissions in your tenant. Members can use existing connections in projects and reports but can’t change credentials or remove datasets.

Troubleshooting

  • Test connection fails immediately — double-check the host, port, and that your network/firewall allows traffic from Summation’s egress IPs.
  • Test connection succeeds but datasets fail to load — usually a permissions issue on the source side. Check that the user/role you provided has read access to the schemas and tables you want.
  • Secrets seem to “disappear” after editing — secret fields are write-only. They render blank after save; the stored value is still there until you overwrite it.
  • Dataset name conflicts — names must be unique across the tenant. Rename in the wizard before deploying.
If a problem persists, copy the error message from the Test connection result and contact support.