Systems | Development | Analytics | API | Testing

Organizations increasingly turn to AI to transform work processes, but this rapid adoption of models has amplified the need for explainable AI. Explaining AI helps us understand how and why models make predictions. For example, a financial institution might wish to use an AI model to automatically flag credit card transactions for fraudulent activity. While an accurate fraud model would be a first step, accuracy alone isn’t sufficient.

Dozens of new connectors, partner integrations, security and compliance enhancements — and the Fivetran data models you love.

For Snowflake CIO and CDO, Sunny Bedi, “life after dashboards” isn’t just a catchy tagline – it’s how he runs his business. At the helm of Snowflake’s 250-person IT and security organization, Bedi oversees a range of strategic initiatives including security and access control, data quality, and general system availability and performance.

The Snowflake Data Cloud is a powerful place to work with data because we have made it easy to do difficult things with data, such as breaking down data silos, safely sharing complex data sets, and querying massive amounts of data. As customers move to the Data Cloud, their needs and timelines vary—our goal is to meet every customer where they are on their Data Cloud journey.

This blog will summarise the security architecture of a CDP Private Cloud Base cluster. The architecture reflects the four pillars of security engineering best practice, Perimeter, Data, Access and Visibility. The release of CDP Private Cloud Base has seen a number of significant enhancements to the security architecture including: Before diving into the technologies it is worth becoming familiar with the key security principle of a layered approach that facilitates defense in depth.