GraphPad Prism vs. IBM SPSS Modeler

If you need to use multiple softwares to compile data such as spreadsheets, another app to run statistics, or another software to make graph and layout, you can try Graphpad Prism because it can do all of this in just a few clicks.

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

• Graphs
• Data analysis
• Layouts

• 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

• The layout feature have been improved over the years but I believe it could be improved by adding more editing tool specially those for images.
• Prism should have more packages for stat analysis.

• 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

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

Incentivized

Graphpad can process multiple steps in just one platform. Database > Stats > Graphs > Layouts > Export

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 improved a lot the way we show data, and therefore it increased our visibility.
• Analysis performed by this software gives credibility.

• 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