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Essential Guide to Using Data Virtualization for Big Data Analytics

Featured Speaker, Mike Gualtieri, Principal Analyst - Forrester Research, Phil Francisco, VP, Data Management Products and  Strategy at IBM and Suresh Chandrasekaran, Senior VP, Data Virtualization at Denodo Technologies.

Business is driving the need for better Analytics - historical, real-time, predictive, and cognitive - across a number of domains including customer, product, operations and more to become more competitive. Mirroring that, the data available to companies for such analytics is exploding in volume and complexity. Companies are adopting a myriad technologies from traditional data warehouses, OLAP tools, DW appliances, Big Data / Hadoop systems and streaming real-time analytics platforms to take advantage of these opportunities.


Mike Gualtieri
Principal Analyst Serving Application Development & Delivery Professionals, Forrester Research, Inc

Phil Francisco
VP, Data Management Products & Strategy IBM

Suresh Chandrasekaran
Senior VP, Data Virtualization Denodo Technologies

 

While each specialized analytics platform delivers the most value in specific areas, overall value to the business is maximized when they are combined into an integrated Analytics Platform using Data Virtualization. It provides cross platform logical views of data and analytic insights across the enterprise and enables flexibility to adapt to new business needs, technology migrations and data sources

Things you will learn:

  •     Key business drivers and patterns for Advanced Analytics
  •     Blueprint for an Integrated Analytics Platform and Logical Data Warehouse
  •     Combining Best in class Analytics Platforms from IBM with Denodo Data Virtualization
  •     Successful Use Case Patterns

 

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