Cloud Adoption

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A Successful Data Strategy for Insurers in Volatile Times (EMEA)

To capitalize on all their data, insurers need a flexible and easily adaptable data integration technology that allows them to keep up with the ever-changing and growing data environment.Data virtualization is that modern data integration technology. It can support insurers not only on their journey to digitization, but also on their future infrastructure changes and innovations, adding agility, flexibility and efficiency to data architectures.Join this webinar to:Find out why data virtualization should be a part of your enterprise data strategySee how this technology can help you capitalize...

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A Successful Journey to the Cloud with Data Virtualization

A shift to the cloud is a common element of any current data strategy. However, a successful transition to the cloud is not easy and can take years. It comes with security challenges, changes in downstream and upstream applications, and new ways to operate and deploy software. An abstraction layer that decouples data access from storage and processing can be a key element to enable a smooth journey to the cloud. Attend this webinar to learn more about:How to use Data Virtualization to gradually change data systems without impacting business operationsHow Denodo integrates with the larger...

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Demo: Cloud Modernization and Data as a Service Option

Mitesh Shah, Senior Cloud Product Manager for Denodo, gives a product demonstration of the data source as an API and managing the API via Denodo Plarform.Watch this demo to learn:How logical data architecture can enable organizations to transition data faster to the cloud with zero downtime and ultimately deliver faster time to insight.

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Cloud Modernization and Data as a Service Option

The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms. Cloud has become a key component of modern architecture design. Data lakes, IoT, NoSQL, SaaS, etc. coexist with relational databases to fuel the needs of modern analytics, ML and AI. Exploring and understanding the data available within your organization is a time-consuming task. Dealing with bureaucracy, different languages and protocols, and the definition of ingestion pipelines to load that data into your data lake can be complex. And all of this without even knowing if that...

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