Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
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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
Analytic Solver
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
Analytic Solver
RapidMiner
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
Community Pulse
Analytic Solver
RapidMiner
Features
Analytic Solver
RapidMiner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Analytic Solver
-
Ratings
RapidMiner
9.5
2 Ratings
13% above category average
Connect to Multiple Data Sources
00 Ratings
10.02 Ratings
Extend Existing Data Sources
00 Ratings
10.02 Ratings
Automatic Data Format Detection
00 Ratings
9.02 Ratings
MDM Integration
00 Ratings
9.01 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Analytic Solver
-
Ratings
RapidMiner
9.0
2 Ratings
7% above category average
Visualization
00 Ratings
9.02 Ratings
Interactive Data Analysis
00 Ratings
9.02 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Analytic Solver
-
Ratings
RapidMiner
8.8
2 Ratings
8% above category average
Interactive Data Cleaning and Enrichment
00 Ratings
9.02 Ratings
Data Transformations
00 Ratings
7.02 Ratings
Data Encryption
00 Ratings
9.02 Ratings
Built-in Processors
00 Ratings
10.02 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Analytic Solver
-
Ratings
RapidMiner
9.0
2 Ratings
7% above category average
Multiple Model Development Languages and Tools
00 Ratings
9.02 Ratings
Automated Machine Learning
00 Ratings
9.02 Ratings
Single platform for multiple model development
00 Ratings
9.02 Ratings
Self-Service Model Delivery
00 Ratings
9.02 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Based on my limited experience and use, and therefore limited global knowledge of the software, I would recommend it especially if the data that will be used as inputs to the model has previously worked on a spreadsheet such as Excel. I would also recommend it to analyze problems of medium and small size. Given the experience I have had when I have used it with large problems, there have been noticeable decreases in the speed of response (which are not associated with the size of the system of equations involved in the calculation). Excellent for processing linear programming models.
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.
On the few occasions when I have used it to deal with problems of optimization of relatively large parameters (with a large number of restrictions and decision variables), the program has been slower, not substantially but slower, than programs such as the WinQsb, even when the latter runs on 32-bit machines and not 64. That has caught my attention, even though it is not a real problem for the uses I give to the program.
Given my partial function as a university professor, it has been much more effective and practical to use other software, due to the limited options that the educational license associated with the software has.
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.
We believe in building the models in Excel. A limitation with Excel is that Excel Solver can not take more than 200 decision variables with multiple constraints. It is cheap in terms of license and maintenance fees against other softwares which are available in the market.
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.
- It has allowed finding ways to optimize (minimizing costs or times) the field processes involved in various projects.
It has even allowed, in specific cases where it was used for that purpose, to optimize the allocation of resources (people) to work in different jobs that present weekly variations of the activity that these people must perform.
It has allowed the sensitivity analysis of projects to changes in the decision variables related to them, which, and in very dynamic and changing environments, resulted in substantial decreases in money losses.
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