A central theme at Snowflake Summit in San Francisco this week was the company’s growing focus on data engineering — and whether it signals a shift from traditional analytics to a dynamic, four-dimensional system of intelligence that can sense, predict and optimize business performance in real time.

TheCUBE analysts George Gilbert and Dave Vellante talk about data engineering during Snowflake Summit.

A 4-D business map can integrate sensing data from people, places, things and activities into real-time information, creating fusion with other platforms and an ability to make future predictions. There were signs this week that Snowflake is interested in making this transition for its business model, but questions remain, according to George Gilbert (pictured, left), principal analyst at theCUBE Research.

“Does Snowflake aspire, with some additional technology, to become the 4-D map for the entire enterprise, or do they become the two-and-a-half-D map, which is dimensions and metrics?” Gilbert said. “It’s a personality change. They have to decide if they want to grow up into that 4-D map. This is going to be the most valuable piece of real estate in enterprise software for the next 10 to 15 years.”

Gilbert spoke with theCUBE’s Dave Vellante (right) at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed key insights from theCUBE’s two days of Summit coverage in San Francisco. (* Disclosure below.)

Seizing the opportunity in data engineering

The announcements from Snowflake this week reflected an interest in helping organizations simplify and scale data movement while boosting analytics performance. The company launched Openflow, designed to simplify ingesting of structured and unstructured data from any source, and Gen1 Standard Warehouse, a doubling of analytics performance without having to alter workloads or queries.

“Data engineering is the opportunity; that’s why they need Openflow, Generation 2 and adaptive compute to go after those engineering workloads,” Vellante said. “Now they are thinking about the full lifecycle, from creation to deletion [of data].”

Snowflake’s attention to engineering workloads this week was designed to address another issue. Some customers were moving data engineering workloads to other vendors over pricing concerns, according to Vellante.

“We talked to enough customers to know it was a problem,” he said. “There was either a real or perceived total cost of ownership problem. Snowflake addressed that in a couple of ways, one being new pricing and also some feature capabilities that appeal. To their credit they didn’t just reprice it, they did the work.”

Snowflake also unveiled a number of enhancements to its Cortex AI platform, including an ability for analysts to employ standard SQL commands to query across diverse data files. The system is backed by widely used large language models from providers such as Meta, OpenAI, Anthropic and Mistral.

“With Cortex Analyst, you are getting a richer structuring of the data,” Gilbert said. “Now it’s moving into the server. The difference is when it’s in the server, this is where Snowflake has a great advantage. That semantic model learns about the data. You’re upleveling the data to a higher level of abstraction.”

In his keynote remarks and media briefing on Monday, Snowflake Chief Executive Sridhar Ramaswamy noted the company’s ongoing commitment to providing customers with tools that are simple to use and engender trust in the data. This has infused the company’s approach to AI and how it can be used in the enterprise.

“Simplicity and trust are the core,” Gilbert said. “The end user can now talk to the data. This is Sridhar’s tent pole issue.”

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

(* Disclosure: TheCUBE is a paid media partner for Snowflake Summit. Neither Snowflake Inc., the primary sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE