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GraphLab picks up $6.75m from Madrona and NEA to bolster its ‘Hadoop for graphs’

GraphLab picks up $6.75m from Madrona and NEA to bolster its ‘Hadoop for graphs’ | big data | Scoop.it

GraphLab-the-company wants to capitalize on the success of GraphLab-the-open-source-project by building a commercial product for applying advanced machine-learning to massive graph datasets, referring to its platform as a “Hadoop but for graphs” on a high level. The company promises to continue actively supporting the open-source project.

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Top 10 Presentations for Learning Hadoop on SlideShare - HadoopWizard

Top 10 Presentations for Learning Hadoop on SlideShare - HadoopWizard | big data | Scoop.it
RT @marcholmes: Fun collection --> RT @meier_manfred: Top 10 Presentations for Learning Hadoop on SlideShare http://t.co/NiEkDzTRCv

Via Armando Reis
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Dell takes SharePlex to Hadoop and beyond

Dell takes SharePlex to Hadoop and beyond | big data | Scoop.it
Dell Software's (formerly Quest's) SharePlex replication tool for Oracle now works with Hadoop...or anything else that can talk to a JMS queue.
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SQL is a Prerequisite Skill for Mainstream Hadoop | #fluentconf - SiliconANGLE (blog)

SQL is a Prerequisite Skill for Mainstream Hadoop | #fluentconf - SiliconANGLE (blog) | big data | Scoop.it
SQL is a Prerequisite Skill for Mainstream Hadoop | #fluentconf
SiliconANGLE (blog)
At the Fluent Conference this week, John Furrier, theCube host, invited Gary Nakamura, CEO of Concurrent Inc.

Via Tony Shan
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Big Data Industry Atlas

Forbes published this chart based on Wikibon data: It’s an $18 billion industry heading to $50 billion in five years, according to tech researchers at Wikibon. Make note of the names in the inner circle.

 

The big data market is still shaping. But soon (not very soon though), we’ll see some clear segments with leaders and challengers. And then…, then we will see a lot of acquisitions and mergers.

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Extending the Data Warehouse with Hadoop

Cloudera believes that the future of Hadoop is as a Platform for Big Data that will complement, not replace, existing data management systems, enabling new ways of interacting with large and diverse data sets. Last week, for example, Cloudera announced the general availability of Cloudera Impala, the industry’s first and only open source interactive SQL framework for the Hadoop platform. Through innovations like Impala, Hadoop presents exciting new opportunities for the enterprise.

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Storing Big Data With Hive: RCFile - Christian Prokopp | Big Data Republic

Storing Big Data With Hive: RCFile - Christian Prokopp | Big Data Republic | big data | Scoop.it
RCFile, as co-developed by Facebook, could be the ideal option for optimized Hive.
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Big Data Analytics For The Masses

Big Data Analytics For The Masses | big data | Scoop.it

Machine learning has historically resided within the realm of the data scientist, a Ph.D.-wielding expert trained to glean insights from big data. But with the rapid expansion of digital information, a move is on to democratize data science tools and put the average business analyst on par (almost) with the data expert.

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The arteries of the world, in Tweets

The arteries of the world, in Tweets | big data | Scoop.it
What happens when you plot billions of geotagged Tweets on a map? You can see the arteries of the world.
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Hip-hip-Hadoop: Data mining for science

Hip-hip-Hadoop: Data mining for science | big data | Scoop.it

The model of distributed calculations, where a problem is broken down into distinct parts that can be solved individually on a computer and then recombined, has been around for decades. But when Google developed the MapReduce algorithm, it added a distinct wrinkle to this method of distributed computing and opened new doors for commercial and scientific endeavors.

Read more at: http://phys.org/news/2013-05-hip-hip-hadoop-science.html#jCphttp://phys.org/news/2013-05-hip-hip-hadoop-science.html


Via Howard Rheingold
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Howard Rheingold's curator insight, May 28, 2013 10:41 PM

Distributed computation and big data meets collective intelligence. Expect this hybrid to develop.

luiy's curator insight, May 29, 2013 7:22 AM

But when Google developed the MapReduce algorithm, it added a distinct wrinkle to this method of distributed computing and opened new doors for commercial and scientific endeavors.

Apache Hadoop is an open-source software framework that evolved from Google's MapReduce algorithm. Many Internet giants—Facebook, Yahoo, eBay, Twitter—rely on Hadoop to crunch data across thousands of computer servers in order to quickly identify and serve customized data to consumers.


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Training Data Scientists

Deploying a new cluster with important, but largely untested technology for scientists is a great first step. But you also have to identify and build a community to take advantage of these emerging tools. TACC has been a leader in education and outreach to the public, offering training, tutorials and university-level instruction on Hadoop as it relates to high-performance parallel computing.

In Fall 2011 and 2012, Xu introduced Hadoop to students in the Visualization and Data Analysis course he co-teaches in the Division of Statistics and Scientific Computing at the university. In addition, Baldridge and Lease jointly designed a new course, "Data-Intensive Computing for Text Analysis," which was offered in Fall 2011, that involved significant use of TACC's Hadoop resources. Interestingly, the course attracted a multi-disciplinary group with 16 computer science students, four iSchool students, three linguistics students, and two electrical and computer engineering students.

At the end of May 2013, Xu will chair a workshop on Benchmarks, Performance Optimization, and Emerging Hardware of Big Data Systems and Applications in conjunction with 2013 IEEE International Conference on Big Data.

Which of the host of new heterogeneous hardware and software technologies available for high-performance clusters are best suited for data-intensive applications? And how can HPC systems be optimally designed to solve big data problems? These are the questions that TACC's Hadoop R&D seeks to answer.



Read more at: http://phys.org/news/2013-05-hip-hip-hadoop-science.html#jCp

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Linfox crunches big data to keep trucks on time

Linfox crunches big data to keep trucks on time | big data | Scoop.it

Logistics giant Linfox is embarking on a big data-crunching exercise that will give its control centres the ability to predict hazards and help drivers navigate around them. 

The company is using a SAP HANA in-memory analytics database engine to crawl about 12 million real-time records generated by telematics equipment on a subset of its 5000-plus truck fleet.

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Hip-hip-Hadoop: Data mining for science - ECNmag.com

Hip-hip-Hadoop: Data mining for science - ECNmag.com | big data | Scoop.it
Hip-hip-Hadoop: Data mining for science
ECNmag.com
Apache Hadoop is an open-source software framework that evolved from Google's MapReduce algorithm.

Via Tony Shan
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Apache Hive 0.11: Stinger Phase 1 Delivered | Hortonworks

Apache Hive 0.11: Stinger Phase 1 Delivered | Hortonworks | big data | Scoop.it

As representatives of this open, community led effort we are very proud to announce the first release of the new and improved Apache Hive, version 0.11.  This substantial release embodies the work of a wide group of people from Microsoft, Facebook , Yahoo, SAP and others. 

 

As promised we have delivered phase 1 of the Stinger Initiative in late spring.  This release is another proof point that that the open community can innovate at a rate unequaled by any proprietary vendor.  As part of phase 1 we promised windowing, new data types, the optimized RC (ORC) file and base optimizations to the Hive Query engine and the community has delivered these key features.

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With Site Ai, Automated Insights Provides A Cliffs Notes Version Of Your Web Analytics | TechCrunch

With Site Ai, Automated Insights Provides A Cliffs Notes Version Of Your Web Analytics | TechCrunch | big data | Scoop.it
Automated Insights, a startup that translates raw data into plain English, is launching a new product that could make analytics data a lot more accessible.
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Luciano Lampi's curator insight, May 24, 2013 8:33 AM

better than a dashboard!

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SuperBowl Sentiment Analysis using Hadoop, Hbase and Twitter4j

SuperBowl Sentiment Analysis using Hadoop, Hbase and Twitter4j | big data | Scoop.it

Via cif, Charles Gerth, Wonil Lee Ph.D.
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This is why big data is the sweet spot for SaaS

This is why big data is the sweet spot for SaaS | big data | Scoop.it

When it comes to using big data technology effectively, there’s a lot to like about SaaS. When companies like BloomReach create and analyze massive web-wide data sets, they automate insights that almost no individual company could discover on its own.

 

http://gigaom.com/2013/05/14/this-is-why-big-data-is-the-sweet-spot-for-saas/

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Scoring Engine Via PMML Makes Hadoop Easier

Scoring Engine Via PMML Makes Hadoop Easier | big data | Scoop.it

Big data application company Concurrent has introduced Pattern, a free and open source "scoring engine" for data professionals to use when deploying machine-learning applications on Apache Hadoop.

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Jacek Bugajski's curator insight, May 27, 2013 5:55 AM

Scoring Engine Via PMML Makes Hadoop Easier

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Texas Advanced Computing Center - Hip-Hip-Hadoop: Data Mining for Science

Texas Advanced Computing Center - Hip-Hip-Hadoop: Data Mining for Science | big data | Scoop.it

The model of distributed calculations, where a problem is broken down into distinct parts that can be solved individually on a computer and then recombined, has been around for decades. Divide-and-conquer techniques allow scientists to predict complex phenomenon from tornado formation to the qualities of nanomaterials to tomorrow's weather forecast.

 

But when Google developed the MapReduce algorithm, it added a distinct wrinkle to this method of distributed computing and opened new doors for commercial and scientific endeavors.

 

Apache Hadoop is an open-source software framework that evolved from Google's MapReduce algorithm. Many Internet giants — Facebook, Yahoo, eBay, Twitter — rely on Hadoop to crunch data across thousands of computer servers in order to quickly identify and serve customized data to consumers.


Via Ashish Umre
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