Using SAS Visual Analytics, enterprises can apply analytics to massive amounts of data; visually explore data at high speed; and share insights via the Web or iPad.
SAS, the world's largest privately owned software maker, has launched
a new in-memory business intelligence software package with a
drag-and-drop graphical interface that brings line-of-business analytics
to a nontechnical audience.
Line-by line queries and scripts are not mandatory here, although they
can be used if necessary. SAS Visual Analytics, the newest product in
SAS's High-Performance Analytics product line launched March 22, offers
an intuitive way to turn virtually any type of corporate data into
useful business insight.
Using SAS Visual Analytics, enterprises can apply analytics to massive
amounts of data, visually explore data at high speed and share insights
via the Web or iPad. The application is designed to run on industry-standard or blade servers.
Cary, N.C.-based SAS, which has been providing business analytics software for
enterprises since 1976, uses its own analytics, in-memory architecture,
intuitive data exploration, Hadoop support and information-delivery
options in the new in-memory Visual Analytics product.
It is the only
in-memory engine designed for business visualization of big
data on inexpensive, nonproprietary hardware, SAS Senior Vice President
Jim Davis told eWEEK.
Hadoop at the Core
A core component of SAS Visual Analytics, the SAS LASR Analytic Server,
uses Hadoop (embedded Hadoop Distributed File System) as local storage
at the server for fault tolerance. SAS LASR Analytic Server has been
tested on billions of rows of data and is extremely scalable, bypassing
the known column limitations of many relational database management
systems, Davis said.
eWEEK witnessed a real-time demonstration of the software March 22 in
San Francisco. The demonstrator simply made a few selections from a
listing of business metrics on the left side of the screen and dropped
them on top of each other into the calculation field, and a graph
immediately appeared, showing the progression of statistics over a set
window of time.
Each one of those queries required millionsor even billionsof
calculations, yet the chart popped up with the results in less than 2
seconds.
"The speed of in-memory architecture offers tremendous benefit.
Organizations can explore huge data volumes and get answers to critical
questions in near-real time," said Dan Vesset, program vice president of
IDC's business analytics research.
"SAS Visual Analytics offers a double bonus: the speed of in-memory
analytics plus self-service eliminates the traditional wait for
IT-generated reports. Businesses today must base decisions on insight
gleaned from data, and that process needs to be close to instantaneous."
Self-Service a Key Attribute
The self-service aspect of this software enables line-of-business users
to move at their own pace, and not have to ask data scientists or other
IT personnel to perform routine queries. It enables IT staff to focus on
more complicated projects.
SAS Visual Analytics includes:
SAS LASR Analytic Server: Clients communicate with SAS LASR Analytic
Server for calculations on the data resident in-memory, producing fast
results.
The Hub: A central location to launch the various elements of SAS Visual Analytics.
Mobile: A tool for viewing reports, connecting to servers and downloading information on the go.
Explorer: An ad hoc data discovery and visualization tool to explore and analyze data.
Designer: Used to create standard and custom reports and dashboards.
Environment Administration: Used by administrators to manage users, security and data.
Server components run on Red Hat or SUSE Linux, and the mobile client
is available for the iPad from the iTunes App Store. Other mobile
devices will be supported in the future, Davis said.
While the high end is not limited, SAS LASR Analytic Server reference
configurations begin with an eight-blade server with 96 processor cores,
768GB of memory and 4.8TB of disk storage, CEO Jim
Goodnight told eWEEK. The upper end of the reference configurations is
96 blades with 1,152 cores, 9.2TB of memory and 57.6TB of disk storage.
"This in-memory analytic engine will extend across our software product
portfolio, applying 35 years of SAS analytics innovation to
big data assets," Goodnight said.
Chris Preimesberger is eWEEK's Editor for Features and Analysis. Twitter: editingwhiz
Chris Preimesberger was named Editor-in-Chief of Features & Analysis at eWEEK in November 2011. Previously he served eWEEK as Senior Writer, covering a range of IT sectors that include data center systems, cloud computing, storage, virtualization, green IT, e-discovery and IT governance. His blog, Storage Station, is considered a go-to information source. Chris won a national Folio Award for magazine writing in November 2011 for a cover story on Salesforce.com and CEO-founder Marc Benioff, and he has served as a judge for the SIIA Codie Awards since 2005. In previous IT journalism, Chris was a founding editor of both IT Manager's Journal and DevX.com and was managing editor of Software Development magazine. His diverse resume also includes: sportswriter for the Los Angeles Daily News, covering NCAA and NBA basketball, television critic for the Palo Alto Times Tribune, and Sports Information Director at Stanford University. He has served as a correspondent for The Associated Press, covering Stanford and NCAA tournament basketball, since 1983. He has covered a number of major events, including the 1984 Democratic National Convention, a Presidential press conference at the White House in 1993, the Emmy Awards (three times), two Rose Bowls, the Fiesta Bowl, several NCAA men's and women's basketball tournaments, a Formula One Grand Prix auto race, a heavyweight boxing championship bout (Ali vs. Spinks, 1978), and the 1985 Super Bowl. A 1975 graduate of Pepperdine University in Malibu, Calif., Chris has won more than a dozen regional and national awards for his work. He and his wife, Rebecca, have four children and reside in Redwood City, Calif.Follow on Twitter: editingwhiz