About a-team Marketing Services
The knowledge platform for the financial technology industry

A-Team Insight Blogs

How to Make the Most of Migrating Big Data and Analytics to Cloud

Subscribe to our newsletter

Migrating big data and analytics workflows to the cloud promises significant cost savings through efficient use of infrastructure resources and software that scales dynamically based on data volume, query load, or both. These are valuable gains for investment banks, but they can only be fully realised by taking a new approach to architecture and software engineering.

Next week’s Data Management Insight webinar will discuss the challenges of migrating to cloud and explain best practice approaches to making the most of moving big data and analytics to cloud. Webinar speakers include Peter Williams, head of partner technology, Global Financial Services, AWS; Ian Lester, vice president, senior principal developer, AI Labs, Nomura; and Daniel Seal, senior vice president, streaming analytics, KX.

Previewing the webinar discussion, Seal says: “To achieve a truly dynamic cloud environment that can scale limitlessly, banks need to transition from legacy architectures to software and databases that natively support horizontal distribution at geographic scale. Microservices architectures are key to this.”

As well as considering how to develop a microservices architecture, the webinar will discuss how to achieve faster delivery by changing your Software Development Lifecycle (SDLC) to support Continuous Integration/Continuous Deployment (CI/CD), and review the benefits you can expect to gain from a successful big data and analytics migration.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: The ROI of Data Trust: Quantifying the Business Value of Data Observability

Data is the fuel that keeps modern financial institutions’ motors running but if that data can’t be trusted then the decisions made based upon it, or the uses to which its put, will be compromised. That’s especially important for data that’s fed into artificial intelligence models. If the data isn’t clean, accurate and complete, then...

BLOG

Governance to be Scrutinised at Inaugural AI in Data Management Summit NYC

Ensuring artificial intelligence deployments are securely governed without stymieing their potential is a delicate balancing act. It requires carefully drawn policies, frameworks and processes. As deployment of the technology expands and its capabilities and complexity multiply, the governance structure must adapt and evolve. How to get this right is among the most important topics swirling...

EVENT

AI in Data Management Summit New York City

Following the success of the 15th Data Management Summit NYC, A-Team Group are excited to announce our new event: AI in Data Management Summit NYC!

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...