In just three months SAS has delivered two significantly upgraded versions of SAS® Visual Analytics.  Most recent was the update it made when they released their new version of SAS Visual Analytics in March 2014. SAS Visual Analytics is basically a high-performance, in-memory solution for exploring any size of data very quickly. It enables you to spot patterns, identify opportunities for further analysis and convey visual results via Web reports, the iPad® or an Android tablet.

The latest version has many updates, including importing the data from 15 additional sources, improved features for data import from massive parallel processing databases, and enhanced features for visualization and reporting.

The tool has on site licensing and options are available for logging onto a SAS-LASR (an in-memory analytics platform for faster computations) server, supported for a non-distributed configuration ( when there is no large data volumes), as well as for a distributed server( for analysing large volumes of data). The flexibility of running directly on the supporting system helps users to overcome the challenge of integration.

In other words if the processing is done directly on the support system resources then no SQL involved algorithms are required. SAS can directly access the Hadoop file system or can run via Map reduce and bring the data into SAS-LASR for high performance computing. Also it supports several Hadoop implementations like Cloudera, Hortonworks, EMC’s pivotal etc. Now importing Twitter data is even easier and faster.

SAS visual analytics has also integrated with SAS office analytics, to provide users the capabilities to display contents in word, excel, power point, outlook, and share point from providers like Bamboo Solutions.

Another interesting feature is that one can now view all the new report features and fix bugs in Android tablets and Apple ipads.

There are also improved features for SAS visual analytics home page, data builder, for visualization and exploration. In the home page users can now hide or reorder the links and applications. In the data builder section users can choose a different fact table and can create the output table as SQL query view. There are many enhanced features for visualization and exploration like an Auto-Update option which helps users to control the automatic update of the visualization after the changes or display frequency for decision trees as a percentage by using a frequency option.

Similarly there are many new features for User interface for designers, for example users can import tables from database servers in addition to importing local files. A new report-level option enables users to put all data queries on hold until the data is updated.  For Reporting, features like geo coordinate map, additional layout for tree maps, or additional transparency options for graphs etc. are also available. Users can add hierarchies based on a date, date time, or time format automatically. One can also now filter the display of LASR tables by user ID. Some of the improved options allow one to manage the self-service import functionality and limit the size of self-service imports.

The SAS Visual Analytics used for data visualization and discovery is now definitely easier and faster and can even handle unstructured data with ease. With more features for reporting and improved mobile capabilities, it is definitely going to be very popular.

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