Organizations today face challenges from rapidly changing markets, new technologies, and the need to build new modern apps running in a multicloud environment. For this reason, business leaders are demanding faster delivery of new applications, services, and insight, requiring greater agility and efficiency from IT. Enterprises, rightly so, are investing in modernizing their on-premises infrastructure with increased use of the cloud.

Although many enterprises are at varying stages in their cloud journeys, most are adopting distributed mixes of on-premises and public cloud environments in order to maintain certain data and applications close by, while making others more accessible and available online. With such distributed cloud networks, core tenants of the enterprise, such as management, scalability and security, become increasingly challenging. There is a path forward, however.

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists. This unprecedented level of big data workloads hasn’t come without its fair share of challenges.

Organizations trust Snowflake with their sensitive data, such as their customers’ personal information. Ensuring that this information is governed properly is critical. First, organizations must know what data they have, where it is, and who has access to it. Data classification helps organizations solve this challenge.

Today’s applications run on data. Customers value applications not only for the functionality they provide, but also for the data itself. It may sound obvious, but without data, apps would provide little to no value for customers. And the data contained in these applications can often provide value beyond what the app itself delivers. This begs the question: Could your customers be getting more value out of your application data?

BigQuery is a serverless, highly scalable, and cost-effective data warehouse that customers love. Similarly, Dataflow is a serverless, horizontally and vertically scaling platform for large scale data processing. Many users use both these products in conjunction to get timely analytics from the immense volume of data a modern enterprise generates.

CDP Private Cloud Base is an on-premises version of Cloudera Data Platform (CDP). This new product combines the best of Cloudera Enterprise Data Hub and Hortonworks Data Platform Enterprise along with new features and enhancements across the stack. This unified distribution is a scalable and customizable platform where you can securely run many types of workloads. CDP is an easy, fast, and secure enterprise analytics and management platform with the following capabilities.

We recently wrote about the interest we’re seeing in connected applications that are built on Snowflake. Connected applications separate code and data such that the app provider creates and maintains the application code, while their customers manage their own data and provide their data platform for processing the application’s data. Some of our partners choose the connected application model because it has benefits for both customers and application providers.

Following the recent GA of Snowpark for our customers on AWS, we’re happy to announce that Snowpark Scala stored procedures are now available in preview to all customers on all clouds. Snowpark provides a language-integrated way to build and run data pipelines using powerful abstractions like DataFrames. With Snowpark, you write a client-side program to describe the pipeline you want to run, and all of the heavy lifting is pushed right into Snowflake’s elastic compute engine.

This post is going to be a bit of a step back into the past. As Mork from Ork would say: “nanu nanu.”