Snowflake

Kadoa configures the integration for you through the Support Center.

Before you begin

A Snowflake role with IMPORT SHARE and CREATE DATABASE privileges. ACCOUNTADMIN has both.
Access to a Snowflake warehouse for queries.

Find your account details:

select
  current_organization_name() as organization_name,
  current_account_name() as account_name,
  current_region() as snowflake_region;

If the query fails, open the account selector in Snowsight and select View account details. Copy the Account/Server URL instead.

Request the integration

Send these details or your Account/Server URL through the Support Center:

Detail	Example
Organization name	`<ORGANIZATION_NAME>`
Account name	`<ACCOUNT_NAME>`
Region	`<SNOWFLAKE_REGION>`
Activity log	Off (default) or on

Historical activity events are not included. Kadoa confirms availability for your region. Accounts in Kadoa’s region use a direct share. Other regions or clouds require a private listing. For a direct share, complete these steps:

Find the share

In Snowsight, open Data sharing > External sharing > Shared with you. Under Ready to Get, select the share whose name starts with KADOA_SHARE_.

Create a database

Enter a database name such as KADOA. Choose the roles that can query it. Select Get Data.

Send the verification code

In your new database, find the schema whose name starts with TEAM_. Replace <KADOA_SCHEMA> with that schema name. If you chose another database name, replace KADOA too:

select verification_nonce
from KADOA.<KADOA_SCHEMA>.connector_verification;

Send the returned code to Support. Kadoa then publishes data to the same database and schema.

For a private listing, open Shared with you > Privately shared listings. Select the listing whose name starts with KADOA_LISTING_. Complete the listing import steps. Support provides the verification instructions for your listing.

Verify the first delivery

Allow about 5 minutes after a workflow run completes. Select your warehouse, database, and Kadoa schema in Snowsight. Find the delivered run and its data view:

select r.job_id, r.schema_version, r.row_count, r.shared_at, v.view_name
from workflow_runs r
join workflow_schema_versions v
  on r.workflow_id = v.workflow_id
  and r.schema_version = v.schema_version
  and r.schema_fingerprint = v.schema_fingerprint
where r.workflow_id = '<WORKFLOW_ID>'
order by r.shared_at desc
limit 20;

Use the returned view_name and job_id to count that run’s rows:

select count(*) as row_count
from <VIEW_NAME>
where job_id = '<JOB_ID>';

Confirm that job_id and the row count match the same run in the Kadoa dashboard.

Query the shared views

View	Contains
`WORKFLOW_RUNS`	Delivered runs, schema versions, row counts, and timestamps
`WORKFLOW_SCHEMA_VERSIONS`	Workflow IDs and their generated view names
`WORKFLOW_SCHEMA_FIELDS`	Field names, types, and positions in `field_order`
`WF_<GENERATED_ID>__V<VERSION>`	Workflow data for one schema version
`WF_<GENERATED_ID>__LATEST`	Workflow data for the latest schema version

Get exact view names from WORKFLOW_SCHEMA_VERSIONS. Do not substitute a workflow ID into a view name. Each data view can contain multiple runs. Filter by job_id to query one run. Versioned views keep their schema when a new version appears. Optional views include ACTIVITY_LOG and TPL_<GENERATED_ID>__LATEST for template data.

Load cloud storage exports with Snowpipe

You can also load files from Amazon S3 or Google Cloud Storage with a Snowpipe you manage. This option uses bucket delivery instead of the native Snowflake share.

Complete a workflow run so a sample data file exists.
Limit the pipe to one workflow’s path and one format, such as Parquet. Exclude other formats and workflow health files.
Configure storage access and automatic loading with Snowflake’s S3 guide or GCS guide.

See file paths for the default layout. If Kadoa hosts your S3 bucket, send Support the pipe’s notification_channel value to configure event notifications.

What’s next

Amazon S3

Set up bucket delivery.

Databricks

Use Delta Sharing.

How data integrations work

See delivery timing, formats, and file paths.

Foundations

Security & Compliance

Build with UI

Build with Code

Integrations

Before you begin

Request the integration

Verify the first delivery

Query the shared views

Load cloud storage exports with Snowpipe

What’s next

Amazon S3

Databricks

How data integrations work

​Before you begin

​Request the integration

​Import the share

​Verify the first delivery

​Query the shared views

​Load cloud storage exports with Snowpipe

​What’s next

Amazon S3

Databricks

How data integrations work

Before you begin

Request the integration

Import the share

Verify the first delivery

Query the shared views

Load cloud storage exports with Snowpipe

What’s next