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
Eva Andreasson, TweetCloudera, Member of Program Advisory Board
Biography: Eva Andreasson
Eva Andreasson has been working with Java virtual machine technologies, SOA, Cloud, and other enterprise middleware solutions for the past 10 years. Joined the startup Appeal Virtual Machines in 2001, as a developer of the JRockit JVM, which later was acquired by BEA Systems. Eva has been awarded two patents on Garbage Collection heuristics and algorithms. She also pioneered Deterministic Garbage Collection which later became productized through JRockit Real Time. Eva has worked closely with Sun and Intel on many technical partnerships, as well as various integration projects of JRockit Product Group, WebLogic, and Coherence (post the Oracle acquisition in 2008). After two years as the product manager for Zing, the worlds most pauseless JVM, at Azul Systems, she joined Cloudera in 2012 to help drive the future of distributed data processing through Cloudera's Distribution of Hadoop.
Twitter: @EvaAndreasson
Presentation: TweetDeep Dive into the Big Data Landscape - Part I
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: TweetDeep Dive into the Big Data Landscape - Part II
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: TweetWhere's Captain Kirk? Charting a Course Through Enterprise Architecture - Part I
Presentation: TweetWhere's Captain Kirk? Charting a Course Through Enterprise Architecture - Part II