The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to drive business outcomes, that is available on the user's cloud platform-of-choice, on-premise, or as a fully-managed service. The solutions include tools providing data preparation enabling users to explore and…
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RapidMiner
Score 8.9 out of 10
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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
DataRobot
RapidMiner
Editions & Modules
No answers on this topic
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
DataRobot
RapidMiner
Free Trial
Yes
No
Free/Freemium Version
Yes
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
Community Pulse
DataRobot
RapidMiner
Features
DataRobot
RapidMiner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
DataRobot
-
Ratings
RapidMiner
9.5
Ratings
13% above category average
Connect to Multiple Data Sources
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10.00 Ratings
Extend Existing Data Sources
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10.00 Ratings
Automatic Data Format Detection
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9.00 Ratings
MDM Integration
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9.00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
DataRobot
-
Ratings
RapidMiner
9.0
Ratings
7% above category average
Visualization
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9.00 Ratings
Interactive Data Analysis
00 Ratings
9.00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
DataRobot
-
Ratings
RapidMiner
8.8
Ratings
8% above category average
Interactive Data Cleaning and Enrichment
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9.00 Ratings
Data Transformations
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7.00 Ratings
Data Encryption
00 Ratings
9.00 Ratings
Built-in Processors
00 Ratings
10.00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
DataRobot
-
Ratings
RapidMiner
9.0
Ratings
7% above category average
Multiple Model Development Languages and Tools
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9.00 Ratings
Automated Machine Learning
00 Ratings
9.00 Ratings
Single platform for multiple model development
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9.00 Ratings
Self-Service Model Delivery
00 Ratings
9.00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
DataRobot can be used for risk assessment, such as predicting the likelihood of loan default. It can handle both classification and regression tasks effectively. It relies on historical data for model training. If you have limited historical data or the data quality is poor, it may not be the best choice as it requires a sufficient amount of high-quality data for accurate model building.
RapidMiner is the best tool to build models on textual data. It is rich in ML algorithms and reduces the need to manually tune the parameters. It automatically optimizes them, thus providing a better solution. RapidMiner again extends great capability for data preparation, its insane connections to almost every data source pulls in the data easily into one environment. And it can comfortably perform data cleaning and process tasks over that. RapidMiner is not so good with image, audio or video data. These data points cannot be used directly in their raw form. They must be transformed into some intermediate form for performing analytics over it. Moreover, there are no connectors to directly pull data from their varied sources. For example, we don't have a connector to read audio data directly from a switch and then convert it to text (although Google speech API is available for audio to text conversion.)
Further improvements to their text analysis tool, to be more like the Qualtrics text analysis tool, would be a great addition. Qualtrics has templates built into their text analysis tool for customer service, quality control, etc, and will automatically slot your text responses into categories associated with certain sub areas of those larger categories.
Wish the tool was more efficient in terms of processing power. The tool takes a lot of CPU processing power, even for a small process on a small data set
Wish there were more options on charts and graphs to visualize the data
DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.
As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.
I've done machine learning through python before, however having to code and test each model individually was very time consuming and required a lot of expertise. The data Robot approach, is an excellent way of getting to a well placed starting point. You can then pick up the model from there and fine tune further if you need.
The other product like RapidMiner Studio that I have used is WEKA. I decided to use RapidMiner because almost all modelling methods and feature selection methods from the Weka machine learning library are available within RapidMiner. Furthermore, RapidMiner Studio is a visual workflow and therefore it is easier to demonstrate and visualise the processes involves in getting the desired results. Visualization of workflow enhances teaching and learning. RapidMiner is rich with algorithms and online learning materials that can assist students in their self-directed learning on data preparation, machine learning, deep learning, text mining, and predictive analytics. Moreover, RapidMiner repository has more than 1500 machine learning algorithms and functions that students can explore for any case study and assignments. The RapidMIner is also an open platform that can seamlessly integrates with other applications programmed with other programming languages like R and Python.