Tag Archives: AtScale

Big Analytics Roundup (September 19, 2016)

Many thanks to Australia’s Dez Blanchfield for his contributions to this roundup. We set out to create a special “Australia/APAC” edition; however, most of the stories have a global interest: chips are chips and deep learning is deep learning wherever you live. We did find this story, profiling a Tasmanian oyster farm that uses Microsoft’s IoT hub. Well, that’s embarrassing. MapR’s

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Big Analytics Roundup (April 4, 2016)

Strata + Hadoop World sparks a number of commercial announcements: AtScale has a new release, Microsoft previews R Server on HDInsight, and IBM puts Spark on a mainframe, FWIW. We also have a nice harvest of explainers and perspectives. Slides from Strata available here. The folks at Domino Data ask: Is XGBoost 10X faster than H2O? We’ll never know the answer, since they

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Big Analytics Roundup (March 21, 2016)

Minimal hard news this week, but some interesting survey results, analysis, articles, explainers and perspectives. — On his personal blog, Will Kurt describes Bayesian reasoning in the Twilight Zone. I tried to learn Bayesian reasoning a few years ago, but it conflicted with my prior beliefs. — Stack Overflow shares results from its 2016 Developer Survey. (h/t Thomas Ott) Key bits:

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Big Analytics Roundup (March 7, 2016)

Hortonworks wins the internet this week beating the drum for its partnership with Hewlett-Packard Enterprise.  The story is down under “Commercial Announcements,” just above the story about Hortonworks’ shareholder lawsuit. Google releases a distributed version of TensorFlow, and HDP releases a new version of Dataflow.  We are reaching peak flow. IBM demonstrates its core values. Folks who fret about cloud security

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Big Analytics Roundup (February 29, 2016)

Happy Leap Day.  Tachyon’s rebranding as Alluxio, release of CaffeOnSpark and GA for Google Cloud Dataproc lead the hard news this week.  The Alluxio announcement has inspired big thinkers to share big thoughts.  And, we have a nice crop of explainers.  Scroll down to the bottom for another SQL on Hadoop benchmark. Explainers — In SearchDataManagement, Jack Vaughn explains Spark

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2015 in Big Analytics

Looking back at 2015, a few stories stand out: Steady progress for Spark, punctuated by two big announcements. Solid growth in cloud-based machine learning, led by Microsoft. Expanding options for SQL and OLAP on Hadoop. In 2015, the most widely read post on this blog was Spark is Too Big to Fail, published in April.  I wrote this post in

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