IBM SPSS Modeler vs. MLReef

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

Works well if you have to involve different roles in different organizations in a project. Less suited when you have a complex system of custom developed tools

• 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

• Helps us to take on more client projects
• Can be used by data analysts as well as casual users

• 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

• Out of the box support for major cloud vendors

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

• 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

• We can handle 4 to 6 times more projects at the same time with our team
• We stay engaged with our customers well beyond the project duration