Data management innovation: JP Morgan’s Fusion & Snowflake transform investing

Robust data management is critical for institutional investors, including pension funds, insurers and mutual funds — as it underpins sound decision-making, effective risk management and regulatory compliance across the vast capital pools they manage.

To meet those needs, JP Morgan Chase & Co. introduced Fusion — a cloud-native platform designed to streamline data management, analytics and reporting throughout the investment lifecycle, according to Gerard Francis (pictured, left), chief product officer of AI and data at JP Morgan.

Snowflake’s Carl Perry and JP Morgan’s Gerard Francis talk with theCUBE about how Fusion is taking data management to the next level.

“When we as JP Morgan launched Fusion, the intent was, how can you take away the data hard work from the customer?” Francis said. “The idea is we onboard the data from the vendors, we normalize it, we harmonize it, we convert it all into one semantic model. We push it back to the customer completely harmonized with analytics on top, so their entire data pain has gone away and they can jump right to value and extracting that from the data.” 

Francis and Carl Perry (right), head of analytics at Snowflake Inc., spoke with theCUBE’s Rebecca Knight and Dave Vellante at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Fusion is leading the charge in data management for institutional investors. (* Disclosure below.)

How Snowflake powers Fusion’s next-gen data management

By leveraging Snowflake’s data cloud capabilities, Fusion provides institutional investors with a powerful, scalable and efficient data management solution. Snowflake facilitates the harmonization of data, enabling institutional investors to better integrate and manage their data resources, according to Francis.

“Snowflake is very important for us because, ultimately, when you have harmonized data for the client, it’s still not good enough because they need to then go off and execute on it in order to get value,” he said. “The customer’s got Snowflake; we push the data fully modeled, fully harmonized, direct to Snowflake, and immediately the client gets value. They can write their queries; they can take advantage of Cortex AI, all of that right off the bat because the data’s been harmonized for them.” 

Since Snowflake Openflow is a fully managed service that enables seamless connectivity between virtually any data source and destination, it represents a significant advancement in data integration, especially for organizations looking to scale their AI and analytics initiatives, according to Perry. Openflow also allows unstructured data to be ingested into Snowflake, enabling organizations to generate insights from a broader range of data sources.

“In particular, Openflow is built on Apache NiFi, an open-source specification that enables us to actually have customers install Openflow and the control plane there into their on-premise, and then have that data pushed into Snowflake,” Perry said. “The reason this is so beneficial is it can pull all of this unstructured data, which is really, you bring the AI to the data, and as you pull that unstructured data into Snowflake, you can have amazing insights. I think Openflow is a game changer for our customers.” 

Snowflake semantic views are a transformative feature designed to enhance AI capabilities and empower business intelligence vendors. They provide a structured, business-friendly abstraction layer over raw data, promoting consistent, reliable insights. By aligning AI-driven outputs with established business definitions, they reduce discrepancies in data interpretation, ensuring that insights remain accurate and trustworthy, according to Perry.

“I think the semantic view work that we’ve been doing, you can now create a semantic view and have it stored inside Snowflake as a top-level object,” he said. “This unlocks pretty much all of the AI capabilities that you’re going to use with Snowflake. It also helps our BI vendors who want to build experiences on top of that semantic model. With all the agents that people are going to be building, this is the critical foundation to have accurate correct answers come back.”

Here’s the complete video interview, 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