GOTO is a vendor independent international software development conference with more that 90 top speaker and 1300 attendees. The conference cover topics such as .Net, Java, Open Source, Agile, Architecture and Design, Web, Cloud, New Languages and Processes

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Dean Wampler, Big Dataist, O'Reilly Author, Member of Program Advisory Board

Dean Wampler

Biography: Dean Wampler

Dean Wampler specializes in the application of Functional Programming principles to “Big Data” applications, using Hadoop and alternative technologies. Dean is a contributor to several open-source projects and the founder of the Chicago-Area Scala Enthusiasts. He is the author of Functional Programming for Java Developers, the co-author of Programming Scala, and the co-author of Programming Hive, all from O’Reilly. He pontificates on twitter, @deanwampler, and at polyglotprogramming.com. His consulting company is Concurrent Thought.

Twitter: @deanwampler

Presentation: Deep Dive into the Big Data Landscape - Part I

Track: Enterprise Architectures - Day 1 / Time: Monday 14:40 - 15:30 / Location: Lille Sal

The Big Data landscape, including Hadoop and NoSQL databases, continues to evolve and mature. New trends include the growth of alternatives to MapReduce, such as Spark, and the resurgent interest in SQL, and the increasing importance of complex event processing at scale. This session will bring you up to date on the state of the art, motivated by example problems that people are solving with Big Data. We’ll explore the landscape and the tools it offers for particular problems. Then we’ll dive into several specific technologies, including Spark for event processing and batch-mode analytics, and new SQL-based options for Big Data.

Presentation: Deep Dive into the Big Data Landscape - Part II

Track: Enterprise Architectures - Day 1 / Time: Monday 15:50 - 16:40 / Location: Lille Sal

The Big Data landscape, including Hadoop and NoSQL databases, continues to evolve and mature. New trends include the growth of alternatives to MapReduce, such as Spark, and the resurgent interest in SQL, and the increasing importance of complex event processing at scale. This session will bring you up to date on the state of the art, motivated by example problems that people are solving with Big Data. We’ll explore the landscape and the tools it offers for particular problems. Then we’ll dive into several specific technologies, including Spark for event processing and batch-mode analytics, and new SQL-based options for Big Data.