Modernizing Integration with Data Virtualization

Presented by

Keath Lewin, Denodo, Mike Mappes, Fusion Alliance and Sajid Patel, Fusion Alliance

About this talk

Today, businesses have more data and data types combined with more complex ecosystems than they have ever had before. Data, Analytics, Data Science and Architecture teams are struggling to provide the business users with the right data as quickly and efficiently as possible to quickly enable analytics, dashboards, BI, reports, etc. Unfortunately, many enterprises seek to meet this pressing need by utilizing antiquated and legacy approaches. There is a better way. Proven by thousands of companies. Join us for this very informative webinar to learn firsthand from Denodo Technologies and our trusted partner, Fusion Alliance how a logical data integration, management and delivery platform powered by data virtualization can become the cornerstone of your modern data approach to deliver data faster and more efficiently than old legacy approaches at enterprise scale. In addition, learn from Fusion Alliance, how they can help you define a data strategy tailored to your organization’s needs and requirements, and how they can help you achieve success and enable your business with self-service capabilities. The first 20 qualified registrants will receive a complimentary lunch pass from Uber Eats. (Lunch pass will be emailed after registering and being approved by Denodo and Fusion Alliance).

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For IT professionals who are focused on data integration and enterprise data management and are overwhelmed by the growing number of data and data types, data virtualization provides real-time integration with agility to access and integrate disparate sources with ease. For business professionals, Data Virtualization brings agile information access that in turn drives business agility. The webcasts provided in this channel by Denodo, the leader in Data Virtualization, provide the latest in common usage patterns, use cases, best practices and strategies for driving business value with data virtualization.