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Many financial services, banks and insurance companies have been struggling to find the optimal solutions and methodologies to leverage their existing stacks in order to ensure the required speed, security and low-latency access to their online platforms across all environments; on-premise, on different cloud vendors and hybrid. 

In parallel, these enterprises are looking to incorporate new, data -driven business processes and applications  that are using AI & ML. They also need to provide their different users (consumers) customized, real-time access to highly sensitive information with a “write once, deploy anywhere” methodology that can work with a on-prem/cloud agnostic software platform.

This session highlights a customer use case from a leading global insurance and asset management company that required a unified data fabric to provide the capabilities of multiple software components. This simplified architecture powered a real-time Data 360 solution that is used by data analysts and operational applications for accurate in-the-moment analytic results.  

We address some of the major challenges faced by enterprises today including:

• Siloed data stores that are used for different data models and applications
• Multi-region deployments with different deployment environments (on-premise, cloud)
• The ability to blend streaming, transactional and historical data for real-time analysis and ML 
• The need for agility and efficient use of microservices
• Real-time “sandboxes” for data scientists or analysts

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