Essential Guide to Using Data Virtualization for Big Data Analytics

Presented by

Mike Gualtieri, Principal Analyst, Forrester

About this talk

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. While each specialized analytics platform deliver the most value in specific areas, yet other overall value to the business is maximized when they are combined into an integrated Analytics Platform using Data Virtualization as an essential component of your overall Analytics strategy. 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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