Schedule: Tutorial sessions

This tutorial provides a solid foundation for those seeking to understand large scale data processing with MapReduce and Hadoop, plus its associated ecosystem. This session is intended for those who are new to Hadoop and are seeking to understand where Hadoop is appropriate and how it fits with existing systems. No programming experience is required. Read more.

Want to extract and process Big Data from the web? This tutorial will show you how to use key open source technologies such as Hadoop, Cascading, Bixo, Tika, Mahout and Solr to create scalable, reliable web mining solutions. Read more.

This hands-on tutorial teaches you how to setup and use Hive, a high-level, data warehouse tool for Hadoop. Hive provides a SQL-like query language, HiveQL, that is easy to learn for people with prior SQL experience, making Hive attractive for data warehousing teams. Hive leverages the power of Hadoop for working with massive data sets without requiring expertise in MapReduce programming. Read more.

This workshop is a jumpstart lesson on how to get from a blank page and a pile of data to a useful data visualization. We'll focus on the design process, not specific tools. Bring your sample data and paper or a laptop; leave with new visualization ideas. Read more.

This tutorial will enable anyone with some programming experience to begin analyzing data with the R programming language Read more.

The big data world is extremely chaotic based on technology in its infancy. Learn how to tame this chaos, integrate it within your existing data environments (RDBMS, analytic databases, applications), manage the workflow, orchestrate jobs, improve productivity and make using big data technologies accessible to a much wider spectrum of developers, analysts and data scientists. Read more.

In this hands-on class, learn how to turn data into effective, interactive visualizations. You do not require a Tableau license to participate, but must bring a Windows laptop or virtual machine. Read more.

This presentation goes beyond the hype, buzzwords, and rehashed slides and actually presents the attendees with a hands-on, step-by-step tutorial on how to write a Java application on top of Apache Cassandra. It focuses on concepts such as idempotence, tunable consistency, and shared-nothing clusters to help attendees get started with Apache Cassandra quickly while avoiding common pitfalls. Read more.

Learn first hand from award-winning Guardian journalists how they mix data, journalism and visualization to break and tell compelling stories: all at newsroom speeds. Read more.

Wouldn't it be great if there were just use two algorithms which could handle most of your predictive modeling needs? It turns out that actually this is the case. Noted machine learning instructor Dr Mike Bowles and champion data miner Jeremy Howard will teach you everything you need to know to apply them successfully. Read more.

Learn now how to use a Hadoop cluster for data analysis using Java MapReduce, Apache Hive and Apache Pig, and get an overview of using the HBase Hadoop database. Some programming experience is strongly recommended for this session. Read more.

While extracting entities from massive amounts of text is a major problem, a proven solution exists. This tutorial will demonstrate a natural language parsing technology to extract entities from all kinds of text using massively parallel clusters. Read more.