Lyndon Maher, Paul McManus discuss data driven development, how to collect data, getting feedback, tools to use, and how to integrate a data-driven mentality into the team.
Sebastian von Conrad advises on reporting: capturing the right data at the right time, best practices and cleaning up reporting debts in code bases.
Sharad Murthy & Tony Ng present Pulsar, a real-time streaming system which can scale to millions of events per second with high availability and 4GL language support.
Matthew Renze introduces the R programming language and demonstrates how R can be used for exploratory data analysis.
Julien Lavigne du Cadet discusses how Criteo uses Druid: an open-source, real-time data store designed to power interactive applications at scale, covering Druid's architecture and internals.
Chris Matts discusses how to manage product mastery, how do we decide whether to use analysis or product management techniques, and what does an end-to-end process looks like.
Tony Quinlan introduces the SenseMaker® method from preparing the ground through gathering experiences and qualitative material to analysis and action planning.
Soumith Chintala introduces deep learning, what it is, why it has become popular, and how it can be fitted into existing machine learning solutions.
Sean Owen introduces Spark, Scala and random decision forests, and demonstrates the process of analyzing a real-world data set with them.
Evelina Gabasova explains how to run a social network analysis on Twitter and how to use data science tools to find out more about followers.
Thore Thomassen shares from experience how to combine structured data in a DWH with unstructured data in NoSQL, and using parallel data warehouse appliances to boost the analytical capabilities.
Peter Harrington explains what you do with machine learning, and what are the building blocks for an application that uses machine learning from collected data to creating predictions for customers.