Seeking to meet growing demand for analytic analysis capabilities, Information Builders yesterday released the version 1.2 upgrade of RStat, the company's module for data mining and statistical analysis.
RStat release 1.2 has been more tightly integrated with the Information Builders' WebFocus BI suite with the new capability to place both products on a single server. RStat previously required a separate statistical server. The key analytic upgrade is the inclusion of survival analysis modeling and scoring routines not previously available.
"Survival analysis is used heavily in the health care and pharmaceutical industries and in social services and related government agencies," says Michael Corcoran, Information Builders' senior vice president and chief marketing officer.
To complement survival analysis, RStat 1.2 offers enhanced charting capabilities. For example, survival charts let analysts visually compare lengths of stay for patients from hospital to hospital or the time children spend in foster care from county to county.
The RStat library of scoring routines has been expanded to include advanced models such as Neural Networks. In addition, testing capabilities have been expanded to including both data mining, standard statistical analysis and conventional hypothesis testing methods, such as T and F tests.
RStat is based on the open-source R programming language, which has more than a million users and a vast library of available functions and algorithms. Corcoran says Information Builders is carefully adding new capabilities from these community sources.
"We don't adopt capabilities right away until we do a fair amount of testing and understand the use and validity of the functionality," he says.
True to open-source practices, the RStat module itself is free, but Information Builders charges annual maintenance and support fees for the software.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.