Audience: Data Users

Content Summary: This page offers a tutorial on how to query data within the Snowflake integration.

Prerequisites:

• Snowflake integration configured with Immuta

• Snowflake tables registered as Immuta data sources

Query Data with Snowflake Governance Controls

With Snowflake Table Grants

Query the data exactly as you would have before Immuta.

Without Snowflake Table Grants

Prerequisite: Users have been granted SELECT privileges on all or relevant Snowflake tables

Query the data exactly as you would have before Immuta.

Query Data without Snowflake Governance Controls

Prerequisite: REVOKE users' access to backing tables

1. Create a new worksheet.

2. Select the appropriate role/database/schema to query the views:

   1. Role: any or just PUBLIC.

   2. Warehouse: any.

   3. Database: The Immuta database name used when configuring the integration (default is IMMUTA).

   4. Schema: The schema that houses the backing tables of your Immuta data sources.

3. Run the following query in the worksheet (replace IMMUTA with the name of your database and replace TABLE.NAME with the name of the backing Snowflake table):

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   SELECT * FROM IMMUTA.TABLE.NAME LIMIT 100

Audience: Data Users

Content Summary: This page offers a tutorial on how to query data within the .

Prerequisites:

• REVOKE users' access to raw tables

Query Data

1. Use your tool of choice to connect to Redshift.

2. Select the Immuta database name used when .

3. Query the Immuta-protected data, which takes the form of immuta_database.backing_schema.table_name:

   1. Immuta Database: The Immuta database name used when .

   2. Backing Schema: The schema that houses the backing tables of your Immuta data sources.

   3. Table Name: The name of the table backing your Immuta data sources.

4. Run your query (it is recommended that you use the catalog in the query). It should look something like this:

Audience: Data Users

Content Summary: This page offers a tutorial on how to query data within the .

Prerequisites:

• REVOKE users' access to raw tables

Query Data

1. Use your tool of choice to connect to Starburst (Trino).

2. Select the Immuta catalog name used when .

3. Query the Immuta-protected data, which takes the form of immuta_catalog.backing_schema.table_name:

   1. Immuta Catalog: The Immuta catalog name used when .

   2. Backing Schema: The schema that houses the backing tables of your Immuta data sources.

   3. Table Name: The name of the table backing your Immuta data sources.

4. Run your query (it is recommended that you use the catalog in the query). It should look something like this:

Audience: Data Users

Content Summary: This page offers a tutorial on how to query data within the Databricks integration.

Prerequisites:

• Databricks integration configured with Immuta

• Databricks tables registered as Immuta data sources

Query Data with Python

1. Create a new workspace.

2. Query the Immuta-protected data, which takes the form of database.table_name:

   1. Database: The database that houses the backing tables of your Immuta data sources.

   2. Table Name: The name of the table backing your Immuta data sources.

3. Run your query, it should look something like:

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   df = spark.sql('select * from database.table_name')
   df.show()

Query Data with SQL

1. Create a new workspace.

2. Query the Immuta-protected data, which takes the form of database.table_name:

   1. Database: The database that houses the backing tables of your Immuta data sources.

   2. Table Name: The name of the table backing your Immuta data sources.

3. Run your query. It should look something like this:

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   select * from database.table_name;

Query Data with SparkR

Establish the User's Identity

1. Create a new workspace.

2. Run:

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   library(SparkR)

Run a Query

1. In the same workspace, but a different cell, query the Immuta-protected data, which takes the form of database.table_name:

   1. Database: The database that houses the backing tables of your Immuta data sources.

   2. Table Name: The name of the table backing your Immuta data sources.

2. Run your query. It should look something like this:

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   df <- SparkR::sql("select * from database.table_name")
   SparkR::head(df)

Query Data with Scala

1. Query the Immuta-protected data, which takes the form of database.table_name:

   1. Database: The database that houses the backing tables of your Immuta data sources.

   2. Table Name: The name of the table backing your Immuta data sources.

2. Run your query. It should look something like this:

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   val sqlDF = spark.sql("select * from database.tablename")
   sqlDF.show()

Audience: Data Users

Content Summary: This page offers a tutorial on how to query data within the Azure Synapse Analytics integration.

Prerequisites:

• Azure Synapse Analytics integration configured with Immuta

• Azure Synapse Analytics tables registered as Immuta data sources

• REVOKE users' access to raw tables

• GRANT users' access to the Immuta schema

Query Data

1. From Synapse Studio click on the Data menu on the left.

2. Click on the Workspace tab.

3. Expand databases and you should see the dedicated pool you specified when configuring the integration.

4. Expand the dedicated pool and you should see the Immuta schema you created when configuring the integration.

5. Select that schema.

6. Select New SQL script and then Empty script.

7. Run your query (note that Synapse does not support LIMIT and the SQL is case sensitive). It should look something like this:

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   SELECT TOP 100 * FROM immuta_schema.backing_database_backing_table;

Audience: Data Users

Content Summary: This page offers a tutorial on how to query data within the Databricks SQL integration.

Prerequisites:

• Databricks SQL integration configured with Immuta

• Databricks SQL tables registered as Immuta data sources

• REVOKE users' access to raw tables

Query Data

1. Select SQL from the upper left menu in Databricks.

2. Click Create → Query.

3. Select the Immuta database name used when configuring the integration.

4. Query the Immuta-protected data, which takes the form of immuta_database.backing_database_table_name:

   1. Immuta Database: The Immuta database name used when configuring the integration.

   2. Backing Database: The database that houses the backing tables of your Immuta data sources.

   3. Table Name: The name of the table backing your Immuta data sources.

5. Run your query (you must include the database). It should look something like this:

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   select * from immuta_database.backing_database_table_name limit 100