Innovative Data Strategies for Advanced Analytics Solutions and the role of Data

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Presented by

Lorrin Ferdinand, Sr. Consultant, Neudesic

About this talk

Data is fueling a new digital economy and compelling companies to rapidly adopt modern technologies such as Machine Learning, AI and Cognitive Science. Consequently, assembling the right blend of data from disparate sources using agile and flexible techniques like logical data warehousing to create purposeful, accessible insights is one of the greatest strategic tasks before us. To address the challenges associated with advanced analytics solutions, Neudesic uses a best-fit-engineering approach to enable enterprises to utilize the right tools for the right job to maximize their data and analytics strategy. When helping customers construct architectures that surface more data to an ever-growing number of data consumers without the need for data replication, Neudesic looks to Denodo as its tool of choice. Join Neudesic and Denodo for an interactive webinar to learn how you can apply data virtualization to your advanced analytics strategy for the purpose of achieving growth objectives. You will get to learn: * Why data virtualization should be part of your advanced analytics strategy. * How easily your use case will fit one of the numerous architecture patterns Denodo enables. * How Denodo’s innovative engine offers best of breed data virtualization capabilities, through a product demonstration.
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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.