Wayne ThompsonGeorgia  Mariani

Predictive Analytics, Machine Learning, and Recommendation Systems on Hadoop

Date: This event took place live on January 30 2014

Presented by: Wayne Thompson, Georgia Mariani

Duration: Approximately 60 minutes.

Cost: Free

Watch the webcast in its original format

In the world of ever growing data volumes, how do you extract insight, trends and meaning from all that data in Hadoop? Do you need help transforming your big data into big knowledge?

Organizations know that the key to competitive advantage is in using advanced analytics to discover trends and use them to your advantage faster than the competition. Getting relevant information from big data requires a different approach. Churning out a couple of analytical models a week isn't going to cut it. If you're using big data to identify trends, spot weaknesses and predict outcomes, you need proven analytical software that's a lot faster, more efficient, accurate, and easy to use.

Join us to learn more about how to reveal insights in your Big data and redefine how your organization solves complex problems.

You will learn how to:

  • Use sophisticated analytics in both a visual interface and a coding interface.
  • Prepare, explore and model multiple scenarios using data volumes never before possible to generate accurate and rapid insights.
  • Interact with the data to add or drop variables into the model and instantly see how their influence provides increased predictive power
  • Easily perform modeling tasks interactively and on-the-fly
  • Quickly understand your model fit with model diagnostics - interactively and in real time (typically in seconds instead of hours or days).
  • Ask what-if questions on all the data.
  • Use a scalable recommendation system to help improve customer experience through profiling users and items and finding how to relate them

About Wayne Thompson

Wayne Thompson is the Manager of SAS Predictive Analytics Product Management 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.

Wayne received his Ph.D. and M.S from the University of Tennessee in 1992 and 1987, respectively. During his PhD program, he was also a visiting scientist at the Institut Superieur d'Agriculture de Lille, Lille, France.

About Georgia Mariani

Georgia Mariani has been with SAS over 15 years. In her current role as the Principal Product Marketing Manager for Statistics she drives marketing direction for SAS' statistics software initiatives.

Prior to her current position, she was the SAS Global Industry Marketing Manager for the Education industry, Georgia lead product and marketing direction by creating and implementing global education initiatives. Before that, Georgia managed analytic strategy at SAS - a role in which she provided analytical product line support for program strategy, sales readiness and channel support. Georgia began her career at SAS as a systems engineer, consulting with sales prospects in the government and education industries regarding their analytical business questions and implementing SAS software and solutions. Before joining SAS, Georgia worked as an analytical consultant to the pharmaceutical industry and as a marketing statistician in the banking industry.

Georgia received her M.S. degree in Mathematics with a concentration in Statistics in 1996 and her B.S. degree in Mathematics in 1992 from the University of New Orleans. During her Master's program she was awarded a fellowship with NASA.

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