InfoQ Homepage Big Data Content on InfoQ
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The Game of Big Data: Scalable, Reliable Analytics Infrastructure at KIXEYE
Randy Shoup describes KIXEYE's analytics infrastructure from Kafka queues through Hadoop 2 to Hive and Redshift, built for flexibility, experimentation, iteration, testability, and reliability.
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The Next Wave of SQL-on-Hadoop: The Hadoop Data Warehouse
Marcel Kornacker presents a case study of an EDW built on Impala running on 45 nodes, reducing processing time from hours to seconds and consolidating multiple data sets into one single view.
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Finding the Needle in a Big Data Haystack
In this solutions track talk, sponsored by Cloudera, Eva Andreasson discusses how search and Hadoop can help with some of the industry's biggest challenges. She introduces the data hub concept.
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JS Optimization Techniques
Guillaume Lathoud suggests expanding JavaScript with mutual tail-call optimization, map/filter/reduce and math computations to obtain faster code.
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A Big Data Arsenal for the 21st Century
In this solutions track talk, sponsored by MongoDB, Matt Asay discusses the differences between some of the NoSQL and SQL databases and when Hadoop makes sense to be used with a NoSQL solution.
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Data Movement at Very Large Scale
In this solutions track talk, sponsored by Solace Systems, Aaron Lee discusses the challenges moving information and techniques that can increase efficiency of data flows within big data architectures
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The World after Cloud Computing & Big Data
Gunter Dueck wonders how are we preparing for the new society marked by cloud computing and big data in which jobs are automated and mediocre abilities are no longer accepted?
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A Research Agenda and Vision for Big Data at NASA
Chris Mattmann covers snow hydrology, regional climate modeling, climate science, and intelligence activities that need advancement to deal with the data deluge across NASA and government agencies.
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Next Gen Hadoop
Akmal B. Chaudhri introduces Apache™ Hadoop® 2.0 and Yet Another Resource Negotiator (YARN).
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What Can Hadoop Do for You?
Eva Andreasson presents typical categories of problems that are commonly solved using Hadoop and also some concrete examples in each category.
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Design Patterns for Large-Scale Real-Time Learning
Sean Owen provides examples of operational analytics projects, presenting a reference architecture and algorithm design choices for a successful implementation based on his experience Oryx/Cloudera.
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Excel Coding Errors Are Destroying World Economies and F# (with Tsunami) Is Here to Stop Them!
Matthew Moloney discusses using F# and .NET inside Excel, demonstrating doing big data, cloud computing, using GPGPU and compiling F# Excel UDFs.
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