In 2018, the art of the possible was the backdrop against which BNY Mellon began developing a modern, integrated data management platform. Foreseeing the need for strategies that support larger analytics and more extensive machine-learning capabilities — and building on its 25-year heritage of award-winning Eagle data solutions — the bank collaborated with early-adopter clients and united its capabilities with Microsoft and Snowflake to create Data Vault and Data Studio.
In removing the complexity and rigid formatting of traditional data management systems, Data Vault has quickly established an ecosystem of data suppliers and consumers. While BNY Mellon data is readily accessible via the platform, clients and third parties can also quickly onboard other data to reduce traditional integration challenges. With Data Vault, clients have the ability to rapidly connect, store, distribute and experiment with quality data across their organization.
Speed Plus Flexibility Equals Empowerment
With cloud-native, modern solutions like Data Vault and Data Studio, the combination of speed and flexibility empowers personnel across the enterprise. As Taylor states, “Today’s tech-savvy, data-hungry business users want access to a larger ecosystem of data, they want to leverage more data to solve a business problem, and they want the flexibility to use their tools of choice when consuming data. That’s exactly what we’re helping clients accomplish right now.”
By enabling end-users across the business to take command of data faster, Data Vault paves the way for rich data experimentation tools. From the front office to the back, financial organizations can investigate data from a single enterprise source using either their tools of choice or Data Studio, a no code environment developed specifically for business users. With Data Studio, clients can experiment with and visualize varied data sets to spark creativity, generate insights and improve decision making. Previously, complex data and analytics had only been within the reach of data scientists and coding experts, but now business users themselves can explore patterns and relationships to extract insights across business disciplines.
Addressing Ongoing Challenges
Managing data at scale is difficult even with the best tools. According to Taylor, most financial organizations he talks to are at some stage of a transformational journey toward the public cloud to help overcome data management issues. Taylor frequently hears about clients’ desire to unlock new potential from larger historical data sets, such as accounting or reference data. In some cases, just accessing the data, not to mention aggregating and gaining insight from it, had been impossible for these clients, because it was trapped in legacy warehouses or only available on the transactional systems.
Moreover, the journey most often cannot be made alone, so organizations must identify the firms they can trust to collaborate with. “Who has the experience and vision to help accelerate and de-risk your transformation agenda?” says Taylor. “That shouldn’t really be a buy versus build decision — it’s about how firms can complement each other on the journey, especially since investment organizations now want more choices and modularity with their capabilities.”
Finally, setting incremental goals is key. According to Taylor, it’s important to demonstrate real value along the way to future goals. Data management now is less about a three- or five-year overhaul and more about demonstrating value-add to the business in a rapid, agile and durable way. One BNY Mellon client, for example, was able to reduce the average time it takes to access new data sets from weeks to hours, thus freeing up time for insight discovery.
There’s no question that the future of data management will be cloud-based. The COVID-19 pandemic has shown that the cloud is resilient, scalable and flexible. In that light, greater adoption of cloud services is inevitable. Recent research indicates that by 2025, “cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives, up from less than 40% in 2021.”¹
In fact, as Taylor explains, “Our clients are telling us to meet them in the cloud. They want access to data without expanding their footprint or rebuilding data pipelines, and they want tools to interact with their data sets, such as our data fabric and data quality engine.” Integrated within Data Vault, BNY Mellon’s data fabric connects data across an organization and makes it available to users anywhere they need it.
As data becomes more and more interconnected, Taylor believes that “how we ask questions and the way that we try to gauge insight will change. Effectively, in the future everything will be a set of interactive data services. We’ll flip in and out of a visual experience—from a business intelligence dashboard to a text-based interaction to a voice-based interaction.”
Yet, regardless of how clients are asking questions and searching for insight, rapid access to high-quality data and analytics is necessary for empowering business users and will remain the key to unlocking data’s value and achieving the best business outcomes.