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
Infor Talent Science
Score8.7 out of 10
N/A
Infor Talent Science is a cloud-based talent intelligence platform that uses Predictive Talent Analytics and pre-employment testing to find the right employees.
The solution leverages large quantities of behavioral and performance data to help organizations build diverse teams and personalized career pathing strategies.
Customized insights from predictive behavioral assessment models help businesses select, retain, and develop the right talent across the entire employee life cycle.
N/A
Pricing
RapidMiner
Infor Talent Science
Editions & Modules
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
No answers on this topic
Offerings
Pricing Offerings
RapidMiner
Infor Talent Science
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Features
RapidMiner
Infor Talent Science
Platform Connectivity
Comparison of Platform Connectivity features of RapidMiner and Infor Talent Science
Feature
RapidMiner
9.5
2 Ratings
13% above category average
Infor Talent Science
-
Ratings
Connect to Multiple Data Sources
10.02 Ratings
00 Ratings
Extend Existing Data Sources
10.02 Ratings
00 Ratings
Automatic Data Format Detection
9.02 Ratings
00 Ratings
MDM Integration
9.01 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of RapidMiner and Infor Talent Science
Feature
RapidMiner
9.0
2 Ratings
7% above category average
Infor Talent Science
-
Ratings
Visualization
9.02 Ratings
00 Ratings
Interactive Data Analysis
9.02 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of RapidMiner and Infor Talent Science
Feature
RapidMiner
8.8
2 Ratings
7% above category average
Infor Talent Science
-
Ratings
Interactive Data Cleaning and Enrichment
9.02 Ratings
00 Ratings
Data Transformations
7.02 Ratings
00 Ratings
Data Encryption
9.02 Ratings
00 Ratings
Built-in Processors
10.02 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of RapidMiner and Infor Talent Science
Feature
RapidMiner
9.0
2 Ratings
6% above category average
Infor Talent Science
-
Ratings
Multiple Model Development Languages and Tools
9.02 Ratings
00 Ratings
Automated Machine Learning
9.02 Ratings
00 Ratings
Single platform for multiple model development
9.02 Ratings
00 Ratings
Self-Service Model Delivery
9.02 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of RapidMiner and Infor Talent Science
Feature
RapidMiner
9.0
2 Ratings
6% above category average
Infor Talent Science
-
Ratings
Flexible Model Publishing Options
9.02 Ratings
00 Ratings
Security, Governance, and Cost Controls
9.01 Ratings
00 Ratings
Talent Intelligence
Comparison of Talent Intelligence features of RapidMiner and Infor Talent Science
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I would recommend Infor Talent Science to other colleagues, particularly those working in structured hiring environments. The platform is great at using behavioral science to improve hiring quality and predict potential outcomes. It has become a valuable tool for our business to help align candidates with roles based on proven success rather than just the interviewers intuition alone.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The platform is well-designed for recruiting and provides detail and actionable insights, but there is a learning curve that prevents it from being completely intuitive out of the gate. From a recruiter’s perspective, the core functionality is strong and reliable. Candidate scorecards, behavioral insights, and interview guides are easy to access once you’re familiar with the system, and the data is presented in a way that supports informed decision-making rather than overwhelming users. The reason for the slightly lower score is that navigation and setup can take time to fully understand, particularly for new users or hiring managers who don’t use the system daily. Some workflows require multiple steps, and certain reports or features are not immediately obvious without training or prior experience.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I have used and evaluated several other talent assessment and hiring platforms, including tools focused on behavioral assessments, personality testing, and skills-based screening. These include solutions similar to Predictive Index–style assessments, generic personality assessments, and ATS-embedded screening tools that offer lighter evaluation capabilities. Compared to many of these options, Infor Talent Science stands out for its depth of behavioral science and predictive accuracy. While some platforms provide surface-level personality insights or one-size-fits-all assessments, Infor Talent Science benchmarks candidates against actual top performers within the organization, which makes the insights far more relevant and actionable.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info