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Enhancing Snowflake With Query-Level Governance

ALTR optimizes your cloud data platform with real-time governance and observability

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Enhancing Snowflake With Query-Level Governance

ALTR optimizes your cloud data platform with real-time governance and observability

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Published on May 13, 2020
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Snowflake's Cloud Data Warehouse (CDW) provides secure and easy access to any data with near-infinite scalability. By enabling seamless consumption and collaboration of shared data across the enterprise, Snowflake customers can make better business decisions while saving valuable time and money. However, the convenience of having all of your data accessible from one platform makes full transparency and control essential.

The Need for Query-Level Data Governance in Snowflake

Even the best CDWs need some help when it comes to managing data access, and data governance more broadly. Snowflake offers straightforward safeguards when it comes to basic user and data access permissions, as well as comprehensive protection for at-rest data so that you can rightly feel comfortable about shipping your data to them.

However, because most security or privacy problems arise from the theft of credentials, and most users of CDWs will have basic access to some sensitive data, tools for observability and governance have to go deeper, to the query level, and be able to mitigate risks.

For each data request, who is accessing which data? How much data are they requesting? When? From Where? These questions are key and can be the difference between preventing a malicious data exfiltration event or a broad privacy exposure, or not.

The Need for Granular Observability in Snowflake

Snowflake's cloud data platform provides advanced analytics and data visualizations. Having all of your data in one platform allows you to supply better insights faster. But what about the insights around how data is being accessed within Snowflake itself?

Snowflake provides a lot of good information about data access natively, but to optimize your cloud data warehouse you must see how it’s being used at a granular level, and apply classification groupings to understand interaction with different data types. Not only can you gain additional insights, but you can then understand the consumption of data with the goal of putting the best policy and rules in place to follow privacy and compliance regulations without disrupting users.

Once you have that in place you can begin to publish that data back into your Snowflake cloud data warehouse for analysis.

How ALTR Fills These Gaps

ALTR's approach pairs the benefits of Snowflake with a solution for data governance and observability that works in parallel — one that’s abstracted, elastic, and has no infrastructure. By using a last-mile, client-side approach, ALTR provides data governance with very little impact on performance.

ALTR optimizes Snowflake by:

  • Governing sensitive data down to the individual query, in real time
  • Tracking and logging all query activity to a granular level that is rich with context
  • Implementing rules and thresholds to govern the flow of data based on time, place, identity, consumption amount, and more

Whether you are a current Snowflake customer or just evaluating the platform, it's important to understand and mitigate the new risks associated with making the most of your valuable data assets.

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