IBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.
$499
per month
RapidMiner
Score 8.8 out of 10
N/A
RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer. RapidMiner’s project-based framework helps to ensure that others can build off their work using visual workflows or automated data science.
$7,500
Per User Per Month
Pricing
IBM SPSS Modeler
RapidMiner
Editions & Modules
IBM SPSS Modeler Personal
4,670
per year
IBM SPSS Modeler Professional
7,000
per year
IBM SPSS Modeler Premium
11,600
per year
IBM SPSS Modeler Gold
contact IBM
per year
Professional
$7,500.00
Per User Per Month
Enterprise
$15,000.00
Per User Per Month
AI Hub
$54,000.00
Per User Per Month
Offerings
Pricing Offerings
IBM SPSS Modeler
RapidMiner
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
IBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop.
IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more.
IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics.
IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.
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 …
The field of data analytics has important value for each organization. IBM SPSS Modeler is one of the leaders in this highly competitive vertical. IBM SPSS is very intuitive compared with others, and has reduced the complexity. This software has various good functionalities …
SPSS and SAS are too expensive. Their interfaces are excellent, but the price point is quite high making them inappropriate for higher education. KNIME is my second choice tool in this space, but it doesn't have the same long established english-speaking user community as …
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.
RapidMiner is really fantastic to perform fast ETL processes and work on your data as you want, no matter what is the source. You will really save a lot of time when you learn how to use it. You can create mining analysis with several algorithms, and thanks to add-ons, you can apply a lot of techniques. It will not replace a business intelligence dashboard but it allows to create great datamarts for your BI tools. One negative thing is that It's no easy to share your outputs.
I am very impressed at how easily you can work within RapidMiner without much data analytics training. Plus with the help of the crowd, you can see what steps others have taken with their data analytics projects.
Text mining was simple and clean. We used this for our call transcription problem where we didn't have the resources to listen to each call. We needed to qualify each call based on some key phrases.
Our direct mail program was large and not very targeted. Using RapidMiner, we were able to isolate a predictive level we felt comfortable with and decided not to send to anyone below that level. We saved quite a bit of money.
I hope RapidMiner would be the first data science platform that allows data scientists to change the behaviour of a machine learning algorithm that already exists in the repository. For example, I want to be able to change the way a genetic algorithm mutates.
Automatic programming: One day, I hope RapidMiner can automatically generate codes in any 4th generation programming language based on the developed model.
More tutorials/samples needed: Why doesn't RapidMiner becomes the next 'UC Irvine Machine Learning Repository'? Provide real examples and real cases for users to study and understand the best practices in modelling. RapidMiner already has some datasets for a tutorial. Besides the existing samples, I hope RapidMiner can provide more sample data and examples.
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.
We tried different data tools and we figured we give RapidMinder Studio a shot as one of our employees had experience with it, and when compared to some of the other tools that we used it was the best fit among the test group that we used. Overall it was a little more fluid and user-friendly.
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.
Thanks to the patters that RapidMiner has detected, we have been able to follow clues in the right direction, both for the Protein Interaction Network Analysis and for the Epilepsy Research
Students and participants of the machine learning workshops have learned about this technology and about the tool