Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK

Empowering data analytics: Real-life use cases

Martin Oberhuber (Think Big, a Teradata company)
12:0512:45 Wednesday, 24 May 2017
Sponsored
Location: Capital Suite 2/3
Average rating: ****.
(4.00, 1 rating)

What you'll learn

  • Learn how leading enterprises have turned their complex data, processes, and organizational models into invaluable insights and business value with modern data analytics

Description

Martin Oberhuber reveals the secrets to successful data science and analytics projects by exploring real-world use cases that illustrate the capabilities needed to develop, deploy, monitor, and maintain analytical processes to seamlessly go from insight to production. Join in to learn how leading enterprises have turned their complex data, processes, and organizational models into invaluable insights and business value with modern data analytics.

This session is sponsored by Teradata.

Photo of Martin Oberhuber

Martin Oberhuber

Think Big, a Teradata company

Martin Oberhuber is a managing partner and principal data scientist at Think Big, a Teradata Company, where he is responsible for Think Big Services in the Western EMEA region. Martin successfully builds and leads cross-functional teams of data scientists, developers, and researchers and helps clients adopt new techniques and processes that empower them to take full advantage of their data. Previously, Martin led the International Data Science practice at Think Big. Martin has a broad range of research, development, and management skills and experience in several sectors, including finance, credit risk, retail, manufacturing, and consumer goods. He is a passionate problem solver with extensive experience developing automated trading strategies and credit risk models using machine learning, quantitative techniques, and big data technologies. Martin holds an MSc in mechanical engineering from the Swiss Federal Institute of Technology and an MSc in computational finance from Carnegie Mellon University.