Wellesley Hills, Mass. – June 8, 2015 – Applying machine learning to Big Data in a Hadoop environment is something all organizations want to do well but few can actually achieve. At this year’s Hadoop Summit North America in San Jose, RedPoint Global Senior Analytics Engineer Bill Porto will address the vital questions, common mistakes and key steps towards successfully implementing machine learning in Hadoop.

Now in its 8th year, Hadoop Summit is the leading conference for the Hadoop community. Over the course of three days, Hadoop thought leaders will showcase successful use cases, development and administration tips and tricks, and educate organizations about how best to leverage Hadoop as a key component in their enterprise data architecture.

During his presentation, Porto will discuss why continual, adaptive optimization is the key to maintaining a leadership position in the market. He will share real-world examples of how to apply predictive modeling and optimization to harness the full power and potential of Hadoop.

WHAT:                 Machine Learning in Big Data – Look Forward or Be Left Behind

WHEN:                 June 9th, 11:15 a.m. PDT.

WHO:                   Bill Porto, Senior Analytics Engineer, RedPoint Global Inc.

WHERE:               San Jose Convention Center, San Jose, CA.

 

About RedPoint Global Inc.

RedPoint Global offers a comprehensive set of world-class ETL, data quality and data integration applications that operate in and across both traditional and Hadoop 2.0/YARN environments. The company also offers data-driven customer engagement solutions that help companies derive insights from customer behaviors and create consistent, relevant and precise messaging across any and all channels. All RedPoint applications offer a unique visual user interface that eliminates the need for programming skills, allowing enterprises to utilize all data to achieve their strategic business goals. For more information please visit www.redpointglobal.com or email us at: contact.us@redpointglobal.com.