When faced endless data and the need to manage it, there are a variety of proven design patterns that will help designers create usable, efficient, and effective interfaces. From distributing workload to reducing sensory overload, we’ll review the techniques that are enabling the highly scalable user interfaces of today and tomorrow.
Data modeling competitions allow companies and researchers to post a problem and have it scrutinised by the world's best data scientists. By exposing a problem to a wide audience, competitions are a great way to get the most out of a dataset. In just a few months, Kaggle's competitions have helped to progress the state of the art in chess ratings and HIV research.
Isabel Drost (Apache Software Foundation/ Nokia Gate 5 GmbH)
With growing amounts of digital data at the fingertips of software developers the need for a scalable, easy to use framework is tremendous. This talk introduces Apache Mahout - a project with the goal of implementing scalable machine learning algorithms for the masses.
This talk demonstrates how an eclectic blend of storage, analysis, and visualization techniques can be used to gain a lot of serious insight from Twitter data, but also to answer fun quesions such as "What does Justin Bieber and the Tea Party have (and not have) in common?"