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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 (at right in photo with eWEEK Editor Chris Preimesberger) 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