IBM SPSS Modeler vs. JMP Pro

Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.

Incentivized

JMP Pro is perfectly suited for statistical analysis but users should have some statistical knowledge before using it since there may be some terms/functions in the software that are not widely used in other fields. No prior coding experience is needed to use JMP Pro. However, most people doing data processing would prefer to code their analysis.

Incentivized

• 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.

Incentivized

• Several types of segmentation models
• Conjoint design
• VERY user-friendly

Incentivized

• Has very old style graphs, with lots of limitations.
• Some advanced statistical functions cannot be done through the menu.
• The data connectivity is not that extensive.
• It's an expensive tool.

Incentivized

• JMP Pro is a really powerful tool for doing statistical analysis. Although the click environment does not require coding experience, new learners will still need to take a long time to know the parameters in the function before performing any analysis.
• The output from JMP Pro analysis (regression analysis) is not always easy to understand, especially when the parameters are programmed differently with the other similar software.

Incentivized

The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources

Incentivized

The online support board is helpful and the free add ons are incredibly appreciated.

Incentivized

When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.

Incentivized

It's much more user-friendly and has a wider statistical toolset.

Incentivized

• Positive - Ease of decision making and reduction in product life cycle time.
• Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
• Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.

Incentivized

• It helped me put together meteorological data from different locations to show which area is the optimal location for wind energy.

Incentivized