Big Data Everywhere Austin
Tuesday, October 27, 2015
Big Data Everywhere Austin is a half-day event focused on Hadoop and surrounding technologies, as well as business applications. Big Data Everywhere will bring together users and developers to share their expertise and experience about these projects. Learn emerging trends from big data industry thought leaders, share best practices with users and developers, and gain valuable insights from some of today's most successful Hadoop deployments.


Using Hadoop to Detect Fraud, Waste and Abuse

Joseph Blue View Bio

Healthcare fraud analytics have traditionally lagged behind advances in commercial fraud detection, but recent big data innovations have narrowed that gap. In this session, you'll learn about the unique challenges presented by Payment Integrity analytics, and how customers are leveraging Hadoop to face those challenges.
Complement Deep Learning with Cheap Learning

Ted Dunning View Bio

Recent results of deep learning on hard problems has set the data world all a titter and made deep learning the fashion of the time. But it is very important to remember that as data expands, the learning problems that are encountered are often nearly green field problems, and it is often possible to solve these problems using remarkably simple techniques. Indeed, on many problems, these simple techniques will give results as good as more complex ones; not because they are profound, but because many problems become simpler at scale. That said, it isn’t always obvious how to do this. In this session, you'll learn about these techniques and how you can apply them in practice.


Joseph Blue

In his role as Data Scientist at MapR, Joe assists customers in solving their big data problems, making efficient use of the Hadoop ecosystem to generate tangible results. Recent projects include debit card fraud & breach detection, lead generation from social data, customer matching through record linkage, lookalike modeling using browser history and real-time product recommendations.

Prior to MapR, Joe was the Chief Scientist for Optum (a division of UnitedHealth) and the principal innovator in analytics for healthcare. As a Sr. Fellow with OptumLabs, he applied machine learning concepts to healthcare issues such as disease prediction from co-morbidities, estimation of PMPY (member cost), physician scoring and treatment pathways. As a leader in the Payment Integrity business, he built anomaly detection engines responsible for saving $100M annually in claim overpayments.

Ted Dunning

Ted Dunning is Chief Application Architect at MapR Technologies and committer and PMC member of the Apache Mahout, Apache ZooKeeper, and Apache Drill projects​. Ted has been very active in mentoring new Apache projects and is currently serving as vice president of incubation for the Apache Software Foundation​.​ Ted was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems. He built fraud detection systems for ID Analytics (later purchased by LifeLock) and he has 24 patents issued to date and a dozen pending. Ted has a PhD in computing science from the University of Sheffield. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting..