Snowflake Snowpark Data Governance and Security

Data Governance and Security Extended to Snowflake Snowpark

Data Governance and Security Extended to Snowflake Snowpark

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Since Snowflake announced the general availability of Snowpark in November 2022, we've heard more and more ALTR customers express interest in utilizing it as part of their Snowflake platform. It provides developers with the capabilities to eliminate complexity and drive increased productivity by building applications and models, or even data pipelines, within one single data platform. We've done some validation and are happy to demonstrate that ALTR's policy enforcement carries over from Snowflake to Snowpark without a hitch.

What is Snowflake Snowpark?

It's essentially a separate execution environment within Snowflake where you can write data-intensive applications. You can use third-party dependencies, and you can process data with very complete programmatic capabilities. This execution environment runs next to the Snowflake SnowSQL interface. ALTR applies, automates, and enforces Snowflake's native data governance features (without requiring SQL) in the Snowflake environment so that when the data flows into Snowpark, the Snowpark environment gets the benefit of all those same policies and controls.  

All the powerful ALTR data governance and security capabilities, including access monitoring, query logs, role-based access controls, dynamic data masking, rate limits, real-time access alerts, and even tokenization, are carried over to the users and data in Snowpark.

Who uses Snowflake Snowpark?

Data scientists are the most common users. If you wanted to use historical data to make a prediction like, for example, using the last ten years of rainfall info to predict the next ten years, you might use something like a statistical or machine learning module. Rather than writing your own, you can pull an existing, already-written module into Snowpark as a dependency and just plumb Snowpark through to build your analysis model. This means the data scientist running these models and analyses in Snowpark can only leverage the data they have permission to access in Snowflake. This kind of protection over sensitive data so approved users can utilize it is critical to financial services organizations. They need to access very sensitive financial data to build models to identify and prevent fraud. Have you ever been contacted by your bank when on vacation in another country to confirm it's really you making the transaction? That's probably a data model identifying anomalous activity.  

How does ALTR benefit Snowflake Snowpark users?

It allows the business to place controls over sensitive data that can be used for data modeling activities. So, the data scientists no longer have to take a chunk of data into their own data silo, crunch on the data, spit out an answer. Through ALTR's single pane of glass, data admins will have total control over all data access in both Snowflake and Snowpark. This also allows data scientists to get the benefits of Snowpark's powerful data processing capabilities with all the Snowflake data they have permission to use – for a streamlined and secure experience.  

Our compatibility with Snowpark is another example of ALTR's goal of providing governance and security over data wherever it is, but it's just the beginning of our Snowpark journey. Keep your eyes out for more details coming at Snowflake Summit 2023 in June.  

Anywhere you want to or need to work with data, ALTR will be there.  

See how ALTR's policy applies to data accessed using Snowpark:

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