GoldenSource joins Snowflake’s native app ecosystem with Omni

Enterprise data management platform GoldenSource is launching a native application called Omni, which will allow institutional investment managers to streamline financial reference data integration. The application aims to make the onboarding of financial reference data easier through access to the GoldenSource data model supported with analytics and reporting on Snowflake’s Data Cloud. Dispersed datasets can now be automatically mapped together and delivered in a digestible format.

Communication lines between GoldenSource and Snowflake first opened in 2021. Jeremy Katzeff, head of buy-side solutions for GoldenSource, was in his first six months at the company when he was introduced to Matt Glickman, who was then kicking off Snowflake’s financial services vertical.

“We’d been kicking around: ‘What does a partnership look like?’” Katzeff tells WatersTechnology. “At that time, Matt said, ‘Well, you have this great data model; maybe figure out a way that we can get that data model integrated.”

GoldenSource’s data model allows capital markets firms to organize and structure pertinent data across different domains. GoldenSource CEO John Eley puts it simply: “Think of it as a horizontal data structure, where all critical operational data has an appropriate home to live in but also can interact with all other operational data.” Glickman believed GoldenSource’s IP was powerful and might pair well with what Snowflake was building for financial services.

Think of it as a horizontal data structure where all critical operational data has an appropriate home in to live but also can interact with all other operational data

John Eley, GoldenSource

Katzeff joined GoldenSource to expand and grow the buy-side platform, trying to determine what areas within the firm could benefit from expansion and investment. He’d previously worked at Broadridge as a senior manager for the fintech’s asset management solutions, and before that, was vice president of global research technology for asset management at JP Morgan. The buy side and its pain points were familiar territory.

“We immediately came to a thought around data warehousing and how people are going to be leveraging that type of platform in the future,” Katzeff says. He points to platforms like Snowflake and its peers, like Databricks, that have made it easy for firms to do it themselves. “So previously, they look to firms like us to do it for them, and we have a warehouse, but where does that go? How do we continue to invest in that product?”

This led to some experimentation on how the IP around the data model could work in a Snowflake type of environment—i.e., a cloud data warehouse.

Around the same time, GoldenSource was in conversation with a UK-based fund company that was looking to build its own data marketplace. It wanted to build its own data warehouse, with the ability to bring in vendor data, curate it, and then make it available internally to stakeholders.

GoldenSource conducted a proof-of-concept that leveraged its data model alongside other modern technology. Ultimately, the fund company went in another direction, but Katzeff says it was a good learning experience and allowed the company to shelve the product for another day.

Building Omni

That day came last spring when GoldenSource re-visited Glickman and Snowflake ahead of the launch of Snowflake’s native applications ecosystem. “Matt came back again and said, it’d be really great if we can do a go-to-market feature here where you build a native app leveraging your data model,” Katzeff says. In about seven weeks, the team coalesced and took what had been built for the fund company and turned it into a native application.

That native application is launching now as Omni.

Traditional AI technologies like machine learning and emerging generative AI tools can work on top of datasets, allowing buy-side participants to analyze portfolio holdings more efficiently as well as examine specific attributes of a portfolio, including ESG exposure. 

Rinesh Patel, global head of industry for financial services at Snowflake, tells WatersTechnology that increasingly, the problem for both the buy side and sell side is a lack of interoperability across platforms. “What you have is a landscape of many platforms for research, order management, execution, data management—all kind of well-intended of course,” he says. “But with these systems, now you get overlapping functionality and more so when certain products are pivoted toward platforms to win more wallet share.” The lack of interoperability across these systems means the data that resides in each is locked in, leading to more challenges and more costs.

In turn, more human resources are spent “pushing and pulling data in and out of systems” to support the pre-trade and post-trade data lifecycles. “That problem just becomes bigger, especially for the buy side, when you think about how the community is investing in and trading more asset classes, fixed income, equities, and new geographies, emerging markets,” Patel says.

This leaves users with a “patchwork of separate technology providers,” Patel says, each with its own database and data model, making reconciliation and retaining accurate positions across portfolios difficult. It’s this problem that Snowflake is looking to solve.

“By bringing that ecosystem together on a common platform or common network, like the financial services data cloud, we can leverage our multi-cloud distribution capabilities, and leverage our data-sharing capabilities to really unlock the silos and unblock the silos and have, effectively and ideally, a single copy of data,” Patel says. “Partners like GoldenSource coming on to that platform really allows our customers to move away from that patchwork that exists, allowing them to be more strategic in how they deliver insights and solve problems.”

Monica Summerville, head of capital markets technology research at Celent, says so far, Snowflake’s strategy in the capital markets appears to be effective. “I think Snowflake’s strategy in capital markets, which seems to be effective, is saying, instead of getting end-users to put all their data in the cloud, maybe we partner with data producers [and] platform providers to host their data, and we provide an environment that makes sense for clients to interact," she says.

Omni will join a growing ecosystem of native applications available on the Snowflake platform. Last summer, data giant Bloomberg rolled out the Bloomberg DL+ Snowflake Native App. It was developed and tested over two months and allows users to incorporate data from Bloomberg Data License Plus (DL+)—the vendor’s cloud-based data management solution, which delivers more than 40,000 data fields spanning 50 million securities—into those applications, which run within clients’ Snowflake accounts. 

Don Huff, global head of client services and operations at Bloomberg Data Management Services, told WatersTechnology that the move was driven by customer demand to be able to access Bloomberg data in Snowflake’s cloud. “Our customers want our data everywhere and anywhere,” he said. “We do have customers taking our data into Snowflake today. Now we have a tool to get them up and running very quickly.”