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Democratizing Data Apps - Snowflake to Acquire Streamlit

Over the past few years, we’ve seen incredible growth in the number of data apps being built on Snowflake, including large customer-facing apps from companies such as BlackRock, Instacart, Lacework, and others. We’re proud of the fact that our platform helps developers bring these applications to life faster, scale better, and provide more powerful insights to their users, whether they be employees, partners, or customers.

Data Classification Now Available in Public Preview

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.

Unlocking New Revenue Models in the Data Cloud

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?

Connected Apps or Managed Apps: Which Model to Implement?

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.

Operationalizing Data Pipelines With Snowpark Stored Procedures, Now in Preview

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.

Piano Brings Advanced Analytics to Customer-Centric Organizations with Snowflake

Piano is a leading provider of software and services that help organizations better understand their audiences across digital channels. With these insights in hand, Piano customers can intelligently serve audiences with personalized experiences that keep them engaged and drive revenue, all through a single unified platform.

Control Issues: Overcoming Departmental Territorialism to Increase Data Sharing

Here’s a scenario that might feel painfully familiar. Your marketing department captures customer leads, and passes them to the sales department. Marketing’s success is measured in part on the number and size of deals that result. But a squabble breaks out over how the sales department handles, nurtures, and attributes those conversions. Result: Neither department really wants to share their data.

Snowflake Unlocks Data Value While Safeguarding Privacy for Both Roku and ViacomCBS

In the past, data leaders had to manage a balancing act between data access and governance. Granting too much access meant opening up the business—and the privacy of consumers—to risk. But if you hold back data, you can’t deliver great experiences and value to customers. The Snowflake Media Data Cloud empowers companies to let go of the balancing act. They now have a single platform to store, govern, and share data while maintaining strict data governance.

Expanding the Data Cloud with Apache Iceberg

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.