TIBCO Statistica™ Integrations

Using Statistica, you can integrate a variety of other analytical platforms into your analyses.

with TIBCO® Spotfire

Statistica™ integrates fully with Spotfire, TIBCO's well-known and popular visualization front-end.

Integration of Statistica™ in Spotfire

Statistica™ workspaces be used by Spotfire as data functions. This allows Statistica™ to be a no code analysis engine for Spotfire users.

Spotfire Integration in Statistica™

You can use Spotfire data connections from within Statistica™. This means that dozens of data sources are now immediately accessible. Load data from Amazon, Cloudera, Hortonworks, Salesforce, SAP HANA, TeraData and many more directly into your workspaces.

with R

The most popular candidates for integration are the programming languages R and Python. Both are available under open source licenses and are developing rapidly.

The R integration has been available in Statistica™ for many years and offers you a wide range of applications:

  • Execute R scripts directly in Statistica™ and automatically work with resulting outputs in Statistica
  • Integration of R scripts in Statistica Visual Basic
  • Providing R functions in nodes in the Statistica™ workspace
  • Centralized management of R-based analyses with user rights and version management using Statistica server
  • Server-based execution of R

You can use R in different ways in Statistica™: On the desktop, centrally managed and executed using the server as a script and integrated into workspace nodes.

R and Statistica™ in validated pharmaceutical environment+
R and Statistica™ on credit risk forecasting+

with Python

The Python programming language can be used in Statistica™ nodes and thus can be integrated into analytical processes. Python is supported in versions 2 and 3, and Statistica™ also comes with its own IronPython engine which is included with every installation of Statistica™. Python has evolved from an elegant programming language to an analytical platform with many functions, especially in the area of deep learning, and thus offers a useful supplement to Statistica™. Python also comes in handy to connect Statistica™ to a multitude of modern APIs as these are often available through python libraries.

with C#

C# is a powerful programming language especially used in application development, but its analytical capabilities are not as extensive as those of R and Python.

Instead C# offers access to the many .Net libraries and can be used for easy interaction with the Windows environment.

with Spark Scala

The integration of Spark Scala differs from other integrations in that it is rather a remote control for Spark. This is a sensible approach since Spark is an environment to perform big data analysis in a cluster with data sets being (usually) too large to be handled by a traditional computer.

A common scenario to benefit from the combination of Statistica™ and Spark is to process the data in the cluster using Spark, reduce it to a manageable size and then import it to Statistica™ to apply complex analytics on it.