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.

Most enterprises that have embarked on their digital business journey have quickly realized that data is the foundation of every digital business. No successful digital business has succeeded without a data strategy. So, when I joined Joe DosSantos, Chief Data Officer at Qlik, on the Data Brilliant podcast, we discussed how data has been democratized, why certain organizations have succeeded with digital transformation, and what factors are required to build the culture for success.

The concept that data is critical to an organization's growth is nothing new. As digital transformation takes every industry by storm, however, the types and sources of data have rapidly evolved. Relying simply on proprietary data is blinding at best. Over the last few years, innovative companies have raced to tap into new sources — often those they don’t own.

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.

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.