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Learn how Data Virtuality enables you to make your data infrastructure more flexible, scalable and future-proof.

Demystifying Data Mesh Q&A with Forrester

Looking to unravel the mystery of Data Mesh? Check out our Q&A paper with Forrester, where we dive into the ins and outs of this revolutionary approach to data architecture.

Data Virtuality Platform SaaS Roadshow

Join us on our roadshow where we will be presenting the Data Virtuality Platform SaaS, the first of its kind on the market.

What you need to know about Data Virtuality Platform SaaS

Data Virtuality Platform SaaS helps data teams reduce the complexity of implementing, operating, and maintaining data virtualization.

Data Governance Strategy for Data Analytics & Data Integration Initiatives

This whitepaper shares the benefits of a mature data governance strategy and how Data Virtuality has aligned its approach to supporting our clients’ varied data governance needs.

The Comprehensive Handbook of Data Integration

This ebook will give you a state-of-the-art overview of all data replication approaches and helps finding the right one for your organization.

The Ins and Outs of Data Mesh

What is the Data Mesh and why is it needed? Enrich your understanding of Data Mesh and how you can enable it with the Data Virtuality Platform.

Data Fabric Q&A Paper with Forrester

In this Q&A paper Noel Yuhanna, VP and Principal Analyst at Forrester, answers frequently asked questions about the Data Fabric architecture.

Best Practices for Hybrid- and Multi-Cloud Architectures

This whitepaper describes best practices for orchestrating Hybrid- and Multi-Cloud architectures and how Data Virtuality can enable these.

Data Architectures for Data Science Using Data Virtualization

In this whitepaper, Rick van der Lans explains how a modern data architecture can help data scientists to be faster and to work more efficiently.

Data Architectures for Data Science Using Data Virtualization Webinar

In this on-demand webinar, we look at how a modern data architecture can help data scientists to be faster and to work more efficiently.

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