Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

Data at scale and speed: Real-world use cases (sponsored by MapR)

Ted Dunning (MapR, now part of HPE)
1:50pm2:30pm Wednesday, March 7, 2018
Location: LL20 B
Average rating: ****.
(4.67, 3 ratings)

What you'll learn

  • Learn how to level up your ability to extract value from data


Getting value from data at large scale and on a variety of time scales is hard. True, it’s not as hard as it used to be, but you still don’t win by default. Ted Dunning explains why it takes good design, the right technology, and a pragmatic approach to succeed.

Using a series of real-world use cases ranging from machine learning pipelines to sensor data processing at the IoT edge to record-setting fraud prevention in finance, Ted demonstrates how you can level up your ability to extract value from data.

This session is sponsored by MapR.

Photo of Ted Dunning

Ted Dunning

MapR, now part of HPE

Ted Dunning is the chief technology officer at MapR, an HPE company. He’s also a board member for the Apache Software Foundation, a PMC member, and committer on a number of projects. Ted has years of experience with machine learning and other big data solutions across a range of sectors. He’s contributed to clustering, classification, and matrix decomposition algorithms in Mahout and to the new Mahout Math library and designed the t-digest algorithm used in several open source projects and by a variety of companies. Previously, Ted was chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems and built fraud-detection systems for ID Analytics (LifeLock). Ted has coauthored a number of books on big data topics, including several published by O’Reilly related to machine learning, and has 24 issued patents to date plus a dozen pending. He holds 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.