Data cloud giant Snowflake’s forum in San Francisco last month was closely watched by the data management industry, especially GoldenSource.
A year after its launch, the creators of GoldenSource’s OMNI data lake product for asset managers were keenly watching what Snowflake had to offer with an eye to enhancing the app’s own provisions for the buy side.
GoldenSource OMNI, which has been built to work natively within the Snowflake Data Cloud, provides portfolio visibility and analytics into private and alternative markets across multiple asset classes. Some of the innovations announced by Snowflake would benefit the app, said GoldenSource Head of Buy-Side Solutions Jeremy Katzeff.“It was particularly exciting to hear about Snowflake’s latest product announcements, which all align very well with the work we’re undertaking to advance GoldenSource OMNI,” Katzeff told Data Management Insight.
Among the innovations that Snowflake announced was a new ingestion service called Snowflake Openflow, which is designed to simplify the movement of data from any source. It uses open standards and Apache NiFi. Katzeff said he saw potential in the service for OMNI.
“Openflow enables a simplification of the integration process which maps perfectly with our efforts to add even more efficiency and reliability to data workflows,” he said. “The potential to leverage these types of new technologies for the continued development of GoldenSource OMNI is very exciting, allowing us to focus on extracting even more value from data for our growing buy-side client base.”
Changing Needs
The buy-side has been proactively digitalising but its peculiar, and rapidly changing, needs have left many participants struggling to find the right technology. A poll of finance and data leaders taken during a recent Data Management Insight webinar found that firms remain dissatisfied with their present data management strategies, with many struggling to deal with challenges such as data silos and inadequate legacy tech stacks.
GoldenSource joined data and technology companies including SimCorp and Rimes in seeking to fill the gaps.
Data Transformation
Katzeff said GoldenSource OMNI was created to provide firms with a holistic view of their data and analytics via a full-featured data lake. The platform offers central governance and flexibility to scale its use and applications. It also encompasses self service data products and models capability so that “teams aren’t constantly ASKING the middle office or investment operations team to constantly fetch data for these individuals”, he said.
GoldenSource, which claims to service some of the top 500 asset managers and asset owners globally, introduced OMNI to meet demands of buy-side firms as their business models evolve to rely heavily on data.
Digitalisation across the financial services sector means all companies need more data and traditionally the buy-side has provided much of that to the sell side and other parts of the industry. Now they are seizing on data to feed their specific operations – managing and balancing portfolios, trading effectively, managing risk, enabling effective client reporting and benchmarking performance. Increasingly, these are being executed in real-time.
“The buy side has various pressures around fees and other factors that they need to be able to scale,” said Katzeff. “And the way that you scale in a services business is investing in technology. So we’re seeing more investment in technology on the buy side, end-to-end.”
The increasing adoption of multi-asset investment strategies has left buy-side firms particularly exposed to compliance risk as they now must satisfy the demands of a broader set of regulators around the world.
“Our model is to centralise everything, help everybody speak the same language, have a common data model, have a common data language, and then that way, after you cleanse and curate and normalise all those different data sets, you can put it into a data lake or an investment data warehouse, like we have on Snowflake,” Katzeff said.
“This makes the data a lot easier to distribute and analyse across those different personas.”
Use Cases
At its forum Snowflake also announced artificial intelligence-powered data science agentic capabilities and upgrades to its Cortex product that will integrates generative AI into SQL queries and accelerate migration from legacy systems. Its data marketplace will also be enhanced with AI-ready data products and third-party content integrations, including real-time news from The Associated Press.
Katzeff said that via Snowflake’s cloud-based platform GoldenSource OMNI customers have been able to deploy it to a variety of use cases. It’s being used to take advantage of the company’s core enterprise data management toolkit and to master their data before deploying it on Snowflake. There it can be combined with other sources of information to power front offices and manage analytics. Another use case is the driving of systematic trading with core reference data, including historical information that goes back a couple of decades.
A singular view of data is important for the utilisation of AI. GoldenSource takes a curated approach to the technology, having observed that the initial rush to adoption had slowed as firms have begun taking time to find the best fit for its deployment.
“They’re exploring very specific use cases: document parsing, summarising, conference calls for research, the quarterly earnings calls and automating some sales and marketing insights in less regulated parts of the business,” he said.
GoldenSource OMNI helps firms achieve AI-led goals as firms “take a cautious view – more so than some other industries”.
“The buy-side are not just data consumers anymore, they’re data producers and want to use that data with customer analytics, investment decision-making and the like,” Katzeff said.
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