Snowflake Summit 2023 brought together industry leaders and experts to unveil the latest innovations in data processing and management.

Among the groundbreaking announcements, container services emerged as a game-changer, promising to address the limitations faced by data scientists and revolutionize the way they work. With its focus on providing a unified data platform for all types of workloads, Snowflake Inc. showcased its commitment to empowering users and expanding their capabilities.

“It’s all data and all code,” said Sanjeev Mohan (pictured, second from right), principal at SanjMo. “It’s a brilliant strategy, because what Snowflake has [concluded] is: ‘We own the data. We should not own all the apps and their underlying theme of this entire conference is security and governance.’”

Tony Baer (left), principal at dbInsights LLC, and Doug Henschen (second from left), vice president and principal analyst at Constellation Research Inc., joined Mohan as they spoke with industry analyst Dave Vellante at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the key takeaways from Day One of Snowflake Summit, with a particular focus on container services and Snowflake’s strategic advancements in the data industry. (* Disclosure below.)

Container services: Addressing limitations and empowering data scientists

Snowflake Summit kicked off with announcements and insights into the future of data processing. One of the highlights of the event was the discussion around container services and its potential to revolutionize the way data scientists work.

Container services address the limitations that data scientists have been facing. The ability to execute directly on the data without the need for user-defined functions is a game-changer for data scientists who prefer a more streamlined and efficient workflow, according to the analysts. The integration of container services within Snowflake provides data scientists with the freedom and flexibility they desire, opening up new possibilities in data processing.

“It’s container services that kind of blows the lid off of Snowflake processing,” Baer said. “It basically addresses all the limitations that data scientists were complaining about. They don’t want to work through UDFs. They want to execute directly on the data, and with container services, you can do exactly that.”

Snowflake’s expansion into all data and all workloads

Another key theme discussed was Snowflake’s commitment to a unified data platform that can handle diverse data types and workloads. The introduction of container services and its seamless integration with various data types and storage options showcased Snowflake’s vision of providing a comprehensive solution for all data-related needs.

By offering native capabilities, such as Document AI and OpenAI, along with containerization options and streamlet usage, Snowflake expands its platform to include multiple ways of accessing machine learning models, the analysts explained. This strategic expansion ensures that Snowflake remains at the forefront of data management and empowers users with a wide range of choices to optimize their workflows.

“We are seeing progress,” Henschen said. “There are things they’re announcing here that customers want in a big way. Lots of cost controls and optimizations. If I were a customer, I’d be asking them to put on the coals to bring these to the fore.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Snowflake Summit:

(* Disclosure: This is an unsponsored editorial segment. However, theCUBE is a paid media partner for Snowflake Summit. Snowflake Inc. and other sponsors of theCUBE’s event coverage have no editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE