IBM provides a data mining and analytics software application named as SPSS modeler. It was originally named Clementine by its creator Integral Solutions Private Limited. SPSS acquired this particular model. When IBM acquired SPSS in 2009, the product was renamed as IBM SPSS modeler. It is available in desktop and server configuration.
Why and where is it preferred?
SPSS modeler provides analytics with the visual modeling capability to leverage productivity improvements. It can consolidate data from multiple file sources from multiple data formats. It has the ability to quickly build models, compare the models, test the models by dividing the input data into testing and training data set and also combine predictive models to provide a better analysis of the data. It helps in pattern detection and in the development of reusable analytical application. SPSS modeler is expert in consolidating and cleaning the data in the fields of marketing, billing, banking or CRM applications.
- Automated modeling, classification and clustering features are available
- Drag and drop features make it easy to use
- Huge amount of data can be processed which is a major issue in traditional prediction using Excel
- Users may or may not be familiar with programming but can create models having a basic understanding of the modeler
- More user friendly compared to writing R scripts or Python
- Available both on-prem and on cloud
- Stable and scalable