With Open Source Solutions the customer benefits from the fact that data sources can be easily managed and validated systems can be built into Statistica. And the customer combines that with the advanced features of R to build complex prediction models.
With Open Source Solutions the customer benefits from the fact that data sources can be easily managed and validated systems can be built into Statistica. And the customer combines that with the advanced features of R to build complex prediction models. With this system, many thousands of parameters are compared and monitored. The results are summarized in reports for specialized departments and authorities.
R and Credit Risk Forecasting
In the financial sector, a customer uses the Open Source Solutions server and R integration to quickly and easily obtain analytical workflows for credit risk forecasting. The simple Open Source Solutions user interface and the ability to use the Open Source Solutions server to manage and deliver R components make customer work easier. At the same time, the effort required to manage r components is reduced.
Other integration options in Open Source Solutions
Python
The R integration of Open Source Solutions is a success story. But there are other possibilities for integration. The Python programming language, for example, can be used in Statistica and therefore can be integrated into analytical processes. Python is compatible with versions 2 and 3, and Statistica also comes with its own IronPython engine, included in all Statistica installations. Python has evolved from an elegant programming language to an analytical platform with many functions, especially in the area of deep learning and therefore offers a useful supplement for Statistica.
C #
Similar to Python, a C# integration is offered (C# is not open source, however). C# is a powerful programming language especially used in application development, but its analytical possibilities are not as extensive as those of R and Python. Instead, C# offers access to many .Net libraries and strong possibilities for interaction with the Windows environment.
Spark Scala
Open Source Solutions offers integration with Spark Scala. This differs from other integrations because it is a Spark remote control. Other integrations, on the other hand, are performed locally by the Open Source Solutions system. This is a sensible approach because Spark is an environment for performing big data analytics on a cluster. The amount of data converted is usually too large for individual computers. Therefore, calculations are stored in a cluster. Spark Scala integration is similar to Python and C# integration, but calculations are done by another system.
System requirements:
CPU: 1.8 GHz dual core processor
RAM: 2 GB
HDD / SSD: 50 GB of free space on the main drive
Operating system: Microsoft Windows 8 32-bit, Microsoft Windows 7 32-bit and Microsoft Windows Vista 32-bit
Resolution: 1024×768
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