In the book, Siegel says that the big secret about Big Data is that it doesn’t really exist. What is big today will be dwarfed by what is coming.

Everything is connected to everything else—if only indirectly—and this is reflected in data. Data always speaks. It always has a story to tell, and there’s always something to learn from it. Data scientists see this over and over again across predictive analytics projects. Pull some data together and, although you can never be certain what you’ll find, you can be sure you’ll discover valuable connections by decoding the language it speaks and listening.”

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In this video from The Next Web Conference Europe 2013, Ken Cukier, Data Editor at the Economist describes how Big Data hype should not deter us from bringing this phenomenon to its full potential to change the world.

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All science is fast becoming what is called data science,” says Bill Howe of UW’s eScience Institute. Today, there are sensors in gene sequencers, telescopes, forest canopies, roads, bridges, buildings, and point-of-sale terminals. Every ant in a colony can be tagged. The challenge is to extract knowledge from this vast quantity of data and transform it into something of value. Lately, Lazowska says, he has been hearing this refrain from researchers in engineering, the sciences, the social sciences, law, medicine, and even the humanities: “I am drowning in data and need help analyzing and managing it.”

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In this video from the 2013 HPC User Forum, John Hengeveld from Intel presents: Big Data Use Cases – The Size of the Data does not define Big Data.

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When we set out to build Hadoop 2.0, we wanted to fundamentally re-architect Hadoop to be able to run multiple applications against relevant data sets. And do so in a way where multiple types of applications can operate efficiently and predictably within the same cluster – this is really the reason behind Apache YARN, which is foundational to Hadoop 2.0. By managing the resource requests across a cluster, YARN turns Hadoop from a single application system to a multi-application operating system.

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In this video from the 2013 HPC User Forum, Steve Conway and Chirag Dekate from IDC present: High-Performance Data Analysis: HPC Meets Big Data.

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In this video from the 2013 HPC User Forum, Darren Schulte from Apixio presents: Knowledge-driven Outcomes for Healthcare.

Apixio delivers actionable insights from textual, scanned, and coded data for optimal risk management, population management, and revenue.”

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In this video from the 2013 HPC User Forum, Radhika Subramanian from Emcien presents: The Big Data Paradigm Shift – Insight Through Automation.

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In this slidecast, Justin Erickson from Cloudera presents a technical overview of Cloudera Impala, an SQL-on-Hadoop solution that enables users to do real-time queries of data stored in Hadoop clusters.

To avoid latency, Impala circumvents MapReduce to directly access the data through a specialized distributed query engine that is very similar to those found in commercial parallel RDBMSs. The result is order-of-magnitude faster performance than Hive, depending on the type of query and configuration.

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In this slidecast, Chris Matty from Versium describes the company’s Real-Life Data Intelligence Platform.

In consumer marketing, LifeData allows ever-narrower segmentation of customers and therefore much more precisely tailored products or services. Greater real life insights about people and businesses enable optimized communication strategies. Sophisticated analytics can predict behavior and greatly improve decision-making. LifeData can make existing applications more intelligent and enable entirely new ones. Versium’s powerful data intelligence platform enables all of this and more.”

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