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

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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.

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