Tag Archives: In-Memory Analytics

SAS in Hadoop: An Update

SAS supports several different products that run “inside” Hadoop based on two different in-memory architectures: (1) The SAS High Performance Analytics suite, originally designed to run in dedicated Teradata and Greenplum appliances, includes five modules: Statistics, Data Mining, Text Mining, Econometrics and Optimization. (2) A second set of products — SAS Visual Analytics, SAS Visual Statistics and SAS In-Memory Statistics for Hadoop

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Spark 1.1 Update

For an overview of Spark, see the Apache Spark Page. On September 11, the Spark team announced release of Spark 1.1.   This latest version of Spark includes a number of significant enhancements: As announced at the Spark Summit, Shark is now converged with Spark SQL.  Databricks has migrated its Shark workloads to Spark, and reports 2X-5X performance improvement. The

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Distributed Analytics: A Primer

Can we leverage distributed computing for machine learning and predictive analytics? The question keeps surfacing in different contexts, so I thought I’d take a few minutes to write an overview of the topic. The question is important for four reasons: Source data for analytics frequently resides in distributed data platforms, such as MPP appliances or Hadoop; In many cases, the

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Smart Money: More Funding for Analytics

Funding for analytic ventures remained robust in January, with 17 significant funding transactions and three acquisitions.   Key themes: Outcomes-based medicine and health care Vertical solutions for the energy industry Solutions for risk management Mobile analytics, including location-based targeting and app metrics Social media sentiment analysis Graph engines (and solutions based on graph engines) In-memory SQL engines All funding news

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Apache Spark for Big Analytics (Updated for Spark Summit and Release 1.0.1)

Updated and bumped July 10, 2014. For a powerpoint version on Slideshare, go here. Introduction Apache Spark is an open source distributed computing framework for advanced analytics in Hadoop.  Originally developed as a research project at UC Berkeley’s AMPLab, the project achieved incubator status in Apache in June 2013 and top-level status in February 2014.  According to one analyst, Apache Spark is among the five

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SAP and SAS Couple Up

SAS and SAP announced a “strategic partnership” today at the SAP TechEd show. According to SAS’ press release, SAP and SAS will partner closely to create a joint technology and product roadmap designed to leverage the SAP HANA® platform and SAS analytics capabilities. By incorporating the in-memory SAP HANA platform into SAS applications and enabling SAS’ industry-proven advanced analytics algorithms

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SAS and Hadoop

SAS’ recent announcement of an alliance with Hortonworks marks a good opportunity to summarize SAS’ Hadoop capabilities.    Analytic enterprises are increasingly serious about using Hadoop as an analytics platform; organizations with significant “sunk” investment in SAS are naturally interested in understanding SAS’ ability to work with Hadoop. Prior to January, 2012, a search for the words “Hadoop” or “MapReduce”

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