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FAST and FURIOUS – Big Data Analytics Meets Hadoop

Wayne Thompson (SAS), Paul Kent (SAS)
Ballroom G

In the world of ever growing data volumes, how do you extract insight, trends and meaning from all that data in Hadoop? Getting relevant information in seconds (instead of hours or days) from big data requires a different approach.
Join us to learn about how to reveal insights in your Big data and redefine how your organization solves complex problems.

This session will showcase how to:

  • reveal insights in your big data and redefine how your organization solves complex problems.
  • prepare, explore and model multiple scenarios using in-memory analytics,
  • model tasks interactively and in real time,
  • ask what-if questions on all the data,
  • instantly add or drop variables into a model and see their influence,
  • assess predictive power,
  • understand your model fit with model diagnostics on the fly
  • use a scalable recommendation system to help improve customer experience
  • and more…

This session is sponsored by SAS

Wayne Thompson

Chief Data Scientist, SAS

Wayne Thompson is the Chief Data Scientist at SAS. He is described as one of the early pioneers of business predictive analytics and is globally renowned presenter, teacher, practitioner and innovator in the field of predictive analytics technology.

He has worked alongside the world’s biggest and most challenging organizations to help them harness analytics to build high performing organizations. Over the course of his 20-year tenure at SAS he has been credited with bringing to market landmark SAS analytics technologies (SAS Text Miner, SAS Credit Scoring for Enterprise Miner, SAS Model Manager, SAS Rapid Predictive Modeler, SAS Scoring Accelerator for Teradata, and SAS Analytics Accelerator for Teradata).

Current focus initiatives include easy to use self-service data mining tools for business analysts, decision management and massively parallel high performance analytics.

Photo of Paul Kent

Paul Kent

VP, Platform R&D, SAS

Paul Kent is Vice President of Big Data initiatives at SAS. He spends his time between Customers, Partners and the Research & Development teams discussing, evangelizing and developing software at the confluence of big data and high performance computing.