THE PROMISE OF THE NEW DATA DOMAIN

Data governance is not just a regulatory requirement but a strategic enabler that ensures integrity and trust in our data whilst driving operational efficiency.

The financial services industry’s insatiable appetite for data necessitates that we have an effective and robust data governance foundation that provides transparency across metadata, driving stronger relationships with clients and stakeholders.”

Debbie Lawrence, Group Head of D&A Data Strategy and Management, LSEG

Big Data has been part of the lexicon for years, underpinning everything from day-to-day operations to cutting-edge innovation. Today—with so much more data to manage—the industry is grappling with how to adapt. While data is ubiquitous across all investment workflows, the things people want to do with data have never been more different.

Now more than ever, the data needs of a company span across numerous spectrums:

Research use cases, where getting quick access to data is the name of the game—and operational use cases that warrant high data quality and rigid service level agreements.

Citizen developers who want quick access to data for rapid micro-innovation—plus traditional IT teams that need locked-down access for production systems.

Traditional markets with established providers and mature datasets—and emerging markets (e.g., privates, crypto) with a less mature ecosystem and less available or mature datasets.

Data to enable new business growth—and to scale existing businesses or workflows.

And these spectrums are only widening. For a long time, companies have met these data needs with tailor-made solutions for each use case. A research use case gets a bespoke research data tool, while a regulatory reporting use case or other middle-office activities each get their own solutions. Increasingly, however, we are seeing a need for these workflows to come together. Research use cases need to have an easy ramp to be promoted into operational production. Citizen developers benefit from operating within the same formality that traditional IT has. The operational demands between enterprise and ad-hoc data sets are converging.

INNOVATIONS

BlackRock’s data platform
A data platform that powers Aladdin’s data factory and the data needs of BlackRock—supporting everything from research datasets to operational IBOR to BlackRock corporate data.

Analytics & investment automation
Users have access to enhanced data discovery that integrates enforcement of Aladdin's data governance policy and provides detailed metadata.

Integrated client data, along with new standard and premium data products designed around end-user personas, are driving research, analytics, and investment automation throughout the portfolio management process.

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DATA: THE KEY INGREDIENT
Christopher Napoli (Snowflake) &
Richard Newman (Aladdin)

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The only way to square these use cases is with a platform approach—eschewing the fragmented model of the past. To keep pace with a changing landscape and stay competitive, companies need an enterprise data platform that supports both structured and unstructured datasets, and has the following qualities:

A sandbox embedded with governance throughout to allow research use cases to scale for enterprise use.

A data marketplace for both citizen developers and IT teams to discover and access data.

The ability to serve both human- and AI-centric processes and needs.

An approach rooted in governance is critical to making this work.

Simply put, firms need to ensure that data can be trusted. Maintaining that trust is only possible if governance is approached systematically. To do this, governance should be woven into the operational workflows—not footnoted as an afterthought or nice-to-have.This exact type of outcome-agnostic platform will ensure your organization is prepared for the (yet unknown) needs of the future—not just the needs of today.Having a mature data platform is a critical step, but how does it plug into the ever-evolving technology landscape?

89%

of Chief Data & Analytics Officers agree that effective data and analytics governance is essential for business and technology innovation.*

*Source: Gartner 2024 Chief Data & Analytics Officers Agenda Survey

Aladdin is betting on an approach of openness, bringing the data platform to wherever people are. Organizations not only need to offer a breadth of access patterns—data shares, APIs, events—but to ensure they are interoperable, with the same surface, shape, and grain. They need to ensure the same semantic models are available across the organization, not confined to any one place. They need to provide the self-service tools (and yes, documentation) to ensure the data is democratized and available to everyone. The technology estate is going to continue to evolve, but through openness we can ensure the data platform remains relevant across paradigms. And by adopting this platform approach within an open architecture, we are seeing that organizations can retain a balance of flexibility and reusability that is pivotal to achieving scale and innovation.

Mr. Nanda's contribution to this article should not be construed as an endorsement by Columbia Threadneedle Investments of any products or services mentioned in the article.

Quantitative modeling in capital markets demands more than advanced algorithms; its success critically depends on access to large, diverse, and integrated datasets.

These include structured and unstructured data spanning multiple asset classes and modalities, ensuring that models learn rich associations and patterns.”

Ioana Boier, Ph.D., Global Head of Capital Markets Strategy, NVIDIA