SAS’ Visual Analytics software has now been adapted to users including work groups and medium-sized businesses
SAS announced that it is making its SAS Visual Analytics available for work groups and medium-sized businesses.
SAS originally introduced SAS Visual Analytics in March 2012 to address big data challenges and leverage the scalability of standard blade computing systems as well as database appliances from EMC Greenplum and Teradata. The new version, now available on hardware platforms typically used as departmental-size servers, brings the power of SAS’ big data solution to departments and work groups regardless of data size.
The SAS Visual Analytics system is an in-memory business intelligence (BI) solution that uses a visual interface to bring potent analytics to a broader class of users to provide a simple and cost-effective path to business insight and better decisions, SAS officials said.
Designed for data of all sizes, SAS’ in-memory solution for exploring data very quickly allows users to examine all data, execute analytic calculations on billions of rows of data in just minutes or seconds, and present results visually, the company said.
With self-service SAS Visual Analytics, executives have instant access, via PCs or tablets, to reports or mobile dashboards that are based on the latest data, allowing them to make quicker, better decisions.
“With powerful data exploration and display abilities, SAS Visual Analytics is more than just a simple business intelligence product. Merging BI and analytics in one, fast, easy-to-use package, SAS sits at the crossroads of several technologies that customers are anxious to see converge,” Jim Davis, senior vice president and chief marketing officer at SAS, said in a statement. “SAS Visual Analytics is highly scalable, ranging from scenarios with a handful of users to a corporate wide, global deployment.”
The new scalability makes SAS Visual Analytics an excellent starting point for organisations seeking data visualisation or wanting to add analytics for fact-based decisions.
Its self-service option for business users to explore data frees IT departments from the constant barrage of information requests. In addition to support for departmental hardware platforms, SAS Visual Analytics now offers new graphical and analytics features, including forecasting, multiple-regress model options, interaction between multiple visuals, dynamic filtering and new visualisations.
A core component of SAS Visual Analytics, the SAS LASR Analytic Server, uses Hadoop as local storage at the server for fault tolerance. SAS LASR Analytic Server has been tested on billions of rows of data and is highly scalable, bypassing the known column limitations of many relational database management systems (RDBMS), the company said.
SAS Visual Analytics enables analysts to look at all data from online sales, stores, external demographic information and social media. Entire populations can be analysed to determine the best offer or interaction rather than using a sample, SAS said.
“SAS Visual Analytics is a fast and easy-to-use solution for our analysts to detect correlations in our business data,” Bernd Butow, managing director at Creditreform, said in a statement. “The result is improved quality and accuracy in forecasting. SAS Visual Analytics is so easy to use that we don’t need additional training.”
SAS High-Performance Analytics Server, another SAS in-memory solution, is also offering new deployment options. Customers who previously required a dedicated blade server rack or a database appliance from Teradata or EMC Greenplum can now run the modelling software on hardware platforms used for other applications.
“Customers unable to justify a dedicated system for SAS High-Performance Analytics Server can now reap its benefits on in-place hardware,” SAS’ Davis said. “With no additional hardware costs, they can run models that once took days or hours in minutes or seconds, and produce business insight on demand on any size data.”
SAS says it has dozens of customers across the globe using the SAS Visual Analytics software, including XL Group, SM Marketing Convergence Inc., the US Internal Revenue Service, the Hong Kong Efficiency Unit and Cosmos Bank.
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Originally published on eWeek.