About a-team Marketing Services
The knowledge platform for the financial technology industry
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: Unpacking Stablecoin Challenges for Financial Institutions

The stablecoin market is experiencing unprecedented growth, driven by emerging regulatory clarity, technological maturity, and rising global demand for a faster, more secure financial infrastructure. But with opportunity comes complexity, and a host of challenges that financial institutions need to address before they can unlock the promise of a more streamlined financial transaction ecosystem. These...

BLOG

12 Companies Bridging Agentic AI and Data Management in Capital Markets

The friction inherent in mobilising data is a perennial problem for financial institutions, who have spent the last decade perfecting the passive data stack – investing heavily in cloud warehouses, governance frameworks and ETL pipelines designed to move data for human consumption. However, the operational reality remains plagued by manual intervention. Recent developments in agentic...

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

Entity Data Management Handbook – Second Edition

Entity data management is this year’s hot topic as financial firms focus on entity data to gain a better understanding of customers, improve risk management and meet regulatory compliance requirements. Data management programmes that enrich the Legal Entity Identifier with hierarchy data and links to other datasets can also add real value, including new business...