The evolution of collaboration in the Data Cloud: Snowflake co-founder weighs in
Evolution and pivoting are integral as companies scale, allowing them to incorporate more features and capabilities in a bid to serve a wider audience, drive expanded business objectives and deliver solutions to more use cases.
Snowflake Inc. started its journey by providing a combined big data and data warehouse solution, infused with an elasticity and simplicity that struck a chord with customers.
†Then we realized that there is one other unique attribute in the cloud that doesn’t exist on-premises, which is collaboration, how you can connect different tenants of the platform together,” said Benoit Dageville (pictured), co-founder and president of products at Snowflake Inc.
Now the next frontier of innovation is data sharing within applications, he added.
Dageville spoke with theCUBE industry analyst Dave Vellante and Lisa Martin at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s live streaming studio. They discussed how Snowflake is evolving its Data Cloud platform to provide more value in collaboration. (* Disclosure below.)
Snowflake’s next 10 years
Snowflake notches a decade of availability in just a couple of months. So, it’s only logical for the company to shape the next 10 years proactively. Its partner ecosystem will be invaluable to the company’s next decade, according to Dageville.
†I really believe that most of Snowflake will not be built by Snowflake,” he said. “And that’s the power of the partners and these applications. When you are going to say, ‘I’m using Snowflake,’ actually, probably you are not going to use something directly co-developed by snowflake. That code will leverage our platform and … you will use a solution that has been built on top of Snowflake.”
A strong example of that strategy in motion is the Apache Iceberg integration, where Snowflake even announced support for hybrid table formats.
“Every thing that you can do with our internal formats, you can do it with Apache iceberg, including securitydefining masking data, masking all the governance that we have, and the finer-grained security aspects, the reputations you can define and the social optimizations you can place on top,” Dageville said.
Supporting the entire application life cycle
On the data programmability front, Snowflake is working to become the unified platform upon which users build data-based applications — with robust coverage of the data science and engineering all the way to interactive, value-added user interfaces, according to Dageville. Its acquisition of Streamlit is a prominent pointer to this commitment.
The data generated around a company’s own data is crucial to create context during analysis, and that’s what makes data collaboration so important, Dageville added. “The data collaboration is critical, and now we expanded it to application and expertise sharing models, for example, and that’s going to have a huge impact,” he said.
Transactional data, thanks to its dynamic nature, is delicate to manage. Unistore, a new Snowflake workload, allows users to combine transactional data sets and directly overlay analytics on them.
“We announced native applications which are fully executed and run inside the data cloud. They need all the services that the application needs and, in particular, managing their states,” Dageville said.
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Snowflake Summit event†
(* Disclosure: TheCUBE is a paid media partner for the Snowflake Summit event. Neither Snowflake, the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
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