# How to Create a Data Source for Data Streamed from Kafka
### 1. Grant DataPancake access to the database, schema, and table
Open a new Snowflake SQL file and run the necessary statements for the database, schema, and table which contain the Kafka data. For example:
GRANT USAGE ON DATABASE DB_NAME TO APPLICATION DATAPANCAKE;
GRANT USAGE ON SCHEMA DB_NAME.SCHEMA_NAME TO APPLICATION DATAPANCAKE;
GRANT REFERENCES, SELECT ON TABLE DB_NAME.SCHEMA_NAME.TABLE_NAME TO APPLICATION DATAPANCAKE;
{% hint style="info" %}
**Imported databases (e.g. Confluent)**: If your Kafka data lives in an imported database, run:
`GRANT IMPORTED PRIVILEGES ON DATABASE DB_NAME TO APPLICATION DATAPANCAKE;`
Use `GRANT IMPORTED PRIVILEGES` on the imported database instead of granting individual privileges on database, schema, and table.
Need help? Read more about [Snowflake shared databases](https://docs.snowflake.com/en/user-guide/data-sharing-gs)
{% endhint %}
### 2. In DataPancake, navigate to the Data Sources page
### 3. Enter a name for the new data source
### 4. Select the data source type
### 5. (Optional) Enter data source tags
These are simply used for filtering / searching. For example: `dev`, `prod`, `api`, `csv`
### 6. Select "Kafka" for the source stream platform
### 7. (Optional) Deduplicate Messages
If checked, two dynamic tables will be produced for the root attributes in the semi-structured data source. The first dynamic table will be used to flatten the root attributes. The second dynamic table will be used to filter the flattened rows using a window function (configured in the next step) to produce the most recent message for each primary key.
### 8. Enter the Deduplication SQL Expression
{% hint style="info" %}
### Required only if "Deduplicate Messages" is toggled on
{% endhint %}
The sql expression used to deduplicate the source stream messages based on a primary key and sort order to produce the most recent message. This value is required if the SQL Code Generation feature is selected and the Deduplicate Messages option is enabled.
### 9. Select the Object Type
### 10. Select the Column Data Type
### 12. Select the Format Type
### 13. Select the Database
### 14. Select the Schema
### 15. Select the Object Name
### 16. Enter the Column Name
This column name can be a sql expression that refers to a specific path of the semi-structured data source. See the example below.
### 17. Click 'Enable Feature Selection'
### 18. Select "SQL Code Generation"
### 19. Select the Output Object Type
### 20. Configure additional settings as needed
[How to configure materialization object & dynamic table settings](/guides/how-to-guides-ui/creating-and-configuring-data-sources/how-to-configure-output-object-and-dynamic-table-settings.md)\
[How to configure the secure view](/guides/how-to-guides-ui/creating-and-configuring-data-sources/how-to-configure-the-secure-semantic-view-layer.md)\
How to configure schema consolidation (WIP)\
[How to configure schema filters](/guides/how-to-guides-ui/creating-and-configuring-data-sources/how-to-configure-schema-filters.md)
### 21. Save the data source
The save button is near the bottom of the page.
### 22. Verify the save completed successfully.
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