---
title: Connecting to Snowflake Data Share
slug: connecting-to-snowflake-data-share
createdAt: 2026-05-07T10:47:24.514Z
---

This guide explains how to access the Altrata Data Feed through a Snowflake private listing, create a shared database, and configure optional change tracking and automation workflows.

### Prerequisites

Your account representative will need your **Snowflake account identifier **in order to share the Altrata private listing with your account.

To find your account identifier, log into Snowsight, click your username in the bottom-left corner, and select **View account details**. Copy the value shown as **Account identifier - **it follows the format `Organization_name-account_name`.

You can also retrieve it by running the following in a Snowflake worksheet:

```sql
SELECT CURRENT_ORGANIZATION_NAME(), CURRENT_ACCOUNT_NAME();
```

### Step 1: Access the Private Listing

1. Sign in to Snowflake. 
2. Navigate to: Data Marketplace → Private Sharing
3. Select the Altrata shared listing. 
4. Click **Get Data**.

### Step 2: Create a Database from the Share

When prompted:

1. Enter a database name.
2. Example `SHARED_ALTRATA_DATAFEED`
3. Assign the appropriate Snowflake role. 
4. Click **Create**.

### Step 3: Grant Internal Permissions

Grant access to internal users or roles within your Snowflake environment.

Example:

```sql
GRANT IMPORTED PRIVILEGES
ON DATABASE SHARED_ALTRATA_DATAFEED
TO ROLE analyst_role;
```

### Step 4: Explore the Shared Data

Connect to the shared database and review available tables.

```sql
USE DATABASE SHARED_ALTRATA_DATAFEED;

SHOW TABLES;

SELECT *
FROM PUBLIC.PERSON
LIMIT 10;
```

### Step 5: Create a Stream for Incremental Changes

Snowflake Streams enable change data capture (CDC) by tracking inserts, updates, and deletes on shared tables.

Example:

```sql
CREATE OR REPLACE STREAM person_stream
ON TABLE SHARED_ALTRATA_DATAFEED.PUBLIC.PERSON;
```

### Step 6: Query Incremental Changes

Retrieve incremental changes captured by the stream.

```sql
SELECT *
FROM person_stream;
```

### Step 7: Process Changes Using MERGE

The following example demonstrates how to merge incremental updates into a target table.

```sql
MERGE INTO person_dailychanges t
USING person_stream s
ON t.person_id = s.person_id

WHEN MATCHED THEN
    UPDATE SET t.value = s.value

WHEN NOT MATCHED THEN
    INSERT (person_id, value)
    VALUES (s.person_id, s.value);
```

### Step 8: Automate Processing with a Snowflake Task (Optional)

You can automate stream processing using a scheduled Snowflake Task.

Example:

```sql
CREATE OR REPLACE TASK process_stream
WAREHOUSE = my_wh
SCHEDULE = '5 MINUTE'
AS

MERGE INTO person_dailychanges t
USING person_stream s
ON t.person_id = s.person_id

WHEN MATCHED THEN
    UPDATE SET t.value = s.value

WHEN NOT MATCHED THEN
    INSERT (person_id, value)
    VALUES (s.person_id, s.value);
```

Enable the task:

```sql
ALTER TASK process_stream RESUME;
```

### Additional Notes

- Ensure the assigned Snowflake role has sufficient privileges to create streams and tasks. 
- Streams only capture changes that occur after the stream is created. 
- Tasks require an active Snowflake warehouse to execute scheduled operations. 
- Replace example object names with naming conventions appropriate for your environment.