IBM SPSS Modeler is a tool that can be used to model and execute Data Science and Data Mining tasks via a graphical user interface. The objective is to make or prepare data-driven decisions to achieve better business results or manage risks.
The IBM SPSS® software platform offers statistical analysis, an extensive library of Machine Learning algorithms, text analytics, Open Source extensibility with Python and R, and integration with Big Data applications. IBM SPSS' ease of use, flexibility, and scalability make it suitable for users of varying skill levels and projects of all sizes and complexity. As a result, using SPSS creates new business opportunities, opportunities to increase efficiency, and opportunities to mitigate risk.
Learn more about IBM SPSS Modeler here.
Here we use IBM SPSS Modeler:
Even though IBM's SPSS Modeler is easy to use, the approach to Data Science and the domain knowledge are crucial for the success of the project. Our consultants are trained in the use of the SPSS Modeler as well as in the approach and the mathematical background. In addition, the Data Scientists are proficient in other programming languages such as R and Python in order to find the optimal solution for the Data Science project. Preferably, we follow CRISP-DM, an approach that has been described and used very successfully by leading vendors and users years ago.