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IBM SPSS Modeler is My Choice
May 10, 2021

IBM SPSS Modeler is My Choice

Tim Daciuk | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with IBM SPSS Modeler

Modeler is used to analyze large amounts of data and to develop and deploy predictive models. The software will look for an appropriate model, assess the quality of models, and create predictions for new data. Modeler can be used in the analysis of numeric data and also with text data. Additionally, text and numeric data can be combined in models if appropriate.
  • Combine text and data
  • Provide facilities for all phases of the data mining process.
  • Use a node and stream paradigm to easily and quickly create models.
  • The graphics are weak.
  • Range of algorithms
  • Easy development environment
  • Ability to customize
  • Quick development.
  • Robust environment to handle the largest dat challenges.
  • Ability to incorporate freeform text.
IBM SPSS Modeler is considerably easier to use. It allows for very rapid development and the ability to get to a goal quickly. There is no need to learn a new programming language so the analyst has the ability to focus on the problem rather than the pedantics of managing code and debugging the program.

Do you think IBM SPSS Modeler delivers good value for the price?

Yes

Are you happy with IBM SPSS Modeler's feature set?

Yes

Did IBM SPSS Modeler live up to sales and marketing promises?

Yes

Did implementation of IBM SPSS Modeler go as expected?

Yes

Would you buy IBM SPSS Modeler again?

Yes

Modeler is well suited for understanding consumer data. The ability to create a prediction and then to understand what is driving that prediction is strong in Modeler. Modeler is closely aligned with the CRISP-DM data mining approach meaning it is not just the 'doing' but also the theoretical background behind the development of data mining models.