SAS High Performance Analytics

Tag Archives: SAS High Performance Analytics

Software for High Performance Advanced Analytics

Posted on February 17, 2015 by Thomas W. Dinsmore One comment

Strata+Hadoop World week is a good opportunity to update the list of platforms for high-performance advanced analytics. Vendors are hustling this week to announce their latest enhancements; I’ll post updates as needed. First some definition. The scope of this analysis includes software with the following properties: Support for supervised and unsupervised machine learning Support for distributed processing Open platform or multi-vendor

2015: Predictions for Big Analytics

Posted on January 7, 2015 by Thomas W. Dinsmore One comment

First, a review of last year’s predictions: (1) Apache Spark matures as the preferred platform for advanced analytics in Hadoop. At the New York Strata/Hadoop World conference in October, if you took a drink each time a speaker said “Spark”, you would struggle to make it past noon. At my lunch table, every single person said his company is currently

News Analysis

SAS Versus R (Part 1)

Posted on December 1, 2014 by Thomas W. Dinsmore 11 comments

Which is better for analytics, SAS or R? One frequently sees discussions on this topic in social media; for examples, see here, here, here, here, here and here. Like many debates in social media, the degree of conviction is often inverse to the quantity of information, and these discussions often produce more heat than light. The question is serious. Many

SAS in Hadoop: An Update

Posted on November 4, 2014 by Thomas W. Dinsmore One comment

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

Architecture

Distributed Analytics: A Primer

Posted on May 1, 2014 by Thomas W. Dinsmore 5 comments

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

Strata Report: Advanced Analytics in Hadoop

Posted on October 25, 2013 by Thomas W. Dinsmore One comment

Here is a quick review of the capabilities for advanced analytics in Hadoop for five vendors at the recent Strata NYC conference: 0xData Alpine Data Labs Oracle SAS Skytree 0XData Product(s) H20 (open source project) h2o (R package) Description Smart people from Stanford with VC backing and a social media program. Services business model with open source software. H20 is an

Products

Jim Goodnight: Big Data is Hype

Posted on October 24, 2013 by Thomas W. Dinsmore One comment

How do you know that SAS has a scalability problem? When Jim Goodnight says you don’t need scalability. “Most of our customers don’t have big data, it’s not that big,” he said in response to a question posed during an on-stage Q&A hosted by Walter Isaacson, president and CEO of the Aspen Institute – and the author of a Steve

News Analysis

SAP and SAS Couple Up

Posted on October 22, 2013 by Thomas W. Dinsmore Leave a comment

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

News Analysis

SAS and Hadoop

Posted on October 21, 2013 by Thomas W. Dinsmore 8 comments

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”

Products

ML/AI

Machine learning. Artificial Intelligence