Senior Technical Manager at a computer software company with 1,001-5,000 employees
Real User
Top 20
2024-05-07T19:24:39Z
May 7, 2024
One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users. I haven't explored the tool's latest version, so I'm unaware of the current features. However, I think it would be beneficial if they could enhance capabilities related to deep neural networks, provide better support for generating UI, and allow for importing and utilizing large language models.
I would appreciate improvements in automation and customization options to further streamline processes. Additionally, it can be challenging to structure formulas and access certain metrics, requiring additional time and effort or searching for information online.
Data Analyst at a tech services company with 1,001-5,000 employees
Real User
Top 20
2023-08-30T08:10:16Z
Aug 30, 2023
In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner. Maybe just go for a more improved interface. We're moving on to 2023, and we're supposed to move forward and keep improving our interface, in my opinion.
Student at a university with 1,001-5,000 employees
Real User
Top 20
2023-05-15T15:46:17Z
May 15, 2023
I do not have any notes for improvement. It's worked fine for the assignment I use it for. It sometimes takes time to load. That issue may be based on my system configuration. I'm not sure if we are able to use custom code from Python. If not, it should. The pricing may be able to be lowered. If they could include video tutorials, people would find that quite helpful.
RapidMiner can improve deep learning by enhancing the features. In the next release, the solution should enhance the features. I think it is a complete solution, but some enhancements would be beneficial.
DATA STRATEGY at a tech services company with 51-200 employees
Real User
2021-06-03T09:45:10Z
Jun 3, 2021
In the Mexican or Latin American market, it's kind of pricey. The pricing can be a bit high. Some of the data science platforms offer much more flexibility. Of course, there's not the same software for visual license results. It's somehow rigid. I'd like to have a module for analytics there. For example, the capability of keeping track of changes in every version would be helpful. It was very, very difficult to track. Even as a partner, it is difficult to keep up with whatever changes they have in mind. On the commercial side, it has been the same. However, since I started, every three months, they propose a different commercial scheme. It's one of the reasons that they got lower marks on the Gardner report. The UI is not super intuitive. It might be nice if, on the first time a person uses the product, there was a wizard that could walk a person through everything. It's supposedly very intuitive, and yet, I don't know what to, I don't know where to click, honestly. They need to offer a better-guided experience for beginners.
I have the deep learning models on my laptop but it doesn't work very well. I think that they should make deep learning models easier. They are using deep learning models today for image processing and language processing.
Senior Manager, Digital Solutions at a tech services company with 1,001-5,000 employees
Real User
2020-01-16T08:44:00Z
Jan 16, 2020
I think it is a fairly straightforward interface generally. It is an easy-to-use solution compared to SAS Enterprise Miner, for example. On the other hand, compared to some other products, maybe the UI could be enhanced. The visual interface could have something like the-drag-and-drop features which Alteryx already supports. Some of those additional features can make RapidMiner a better tool and maybe more competitive or advanced.
When I started using RapidMiner, I found it difficult to get it to read the metadata. I wanted to use, for example, a pivot table, and it did not have the variable or the attribute names in it. There were no values. It took a long while to figure out how to do that, although it tends to do it automatically nowadays. RapidMiner is not utterly intuitive for beginners. Sometimes people have trouble distinguishing between a file in their own file system and a repository entry, and they cannot find their data. This is an area where this solution could be improved. It would be helpful to have some tutorials on communicating with Python. I found it a bit difficult at times to figure out which particular variable, or attribute, is going where in Python. It is probably a simple thing to do but I haven't mastered it yet. I'd like them to do a video on that. There are a large number of videos that are usually well-produced, but I don't think that they have one on that. Essentially, I would like to see how to communicate from RapidMiner to Python and from Python to RapidMiner. One of the things I do a lot of is looking at questionnaires where people have used Likert-type scales. I don't recommend Likert-type scales, but if they're properly produced, which is a lot of hard work and it's not usually done, they're really powerful and you can do things like normalizing holes on the Likert scale. That's not the same as normalizing your data in RapidMiner. So, I would want to get results with these Likert scales, pass it through RapidMiner, do a normalization and pass back both the raw scores and the normalized scores and put in some rules, which will say if it's high on the raw score and on the normalized score and low on the standard deviation, then you can trust it.
The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator.
I think it's a great product but confusing in some way with regard to the user interface and integration with other tools. An improvement would be the addition of some buttons which would be useful because I'm sometimes unsure why I need to use something or what is its purpose. I would say the same goes for additional features, the addition of buttons would be helpful. The product is better than other software that I use.
I would like to see all users have access to all of the deep learning models, and that they can be used easily. RapidMiner loads very slowly, which is something that should be improved.
RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.
The product must provide data-cleaning features. I could not use RapidMiner for data cleaning in one of my projects and had to use Python instead.
One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users. I haven't explored the tool's latest version, so I'm unaware of the current features. However, I think it would be beneficial if they could enhance capabilities related to deep neural networks, provide better support for generating UI, and allow for importing and utilizing large language models.
I would appreciate improvements in automation and customization options to further streamline processes. Additionally, it can be challenging to structure formulas and access certain metrics, requiring additional time and effort or searching for information online.
I would like to see more integration capabilities.
In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner. Maybe just go for a more improved interface. We're moving on to 2023, and we're supposed to move forward and keep improving our interface, in my opinion.
I do not have any notes for improvement. It's worked fine for the assignment I use it for. It sometimes takes time to load. That issue may be based on my system configuration. I'm not sure if we are able to use custom code from Python. If not, it should. The pricing may be able to be lowered. If they could include video tutorials, people would find that quite helpful.
RapidMiner can improve deep learning by enhancing the features. In the next release, the solution should enhance the features. I think it is a complete solution, but some enhancements would be beneficial.
Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there.
In the Mexican or Latin American market, it's kind of pricey. The pricing can be a bit high. Some of the data science platforms offer much more flexibility. Of course, there's not the same software for visual license results. It's somehow rigid. I'd like to have a module for analytics there. For example, the capability of keeping track of changes in every version would be helpful. It was very, very difficult to track. Even as a partner, it is difficult to keep up with whatever changes they have in mind. On the commercial side, it has been the same. However, since I started, every three months, they propose a different commercial scheme. It's one of the reasons that they got lower marks on the Gardner report. The UI is not super intuitive. It might be nice if, on the first time a person uses the product, there was a wizard that could walk a person through everything. It's supposedly very intuitive, and yet, I don't know what to, I don't know where to click, honestly. They need to offer a better-guided experience for beginners.
I have the deep learning models on my laptop but it doesn't work very well. I think that they should make deep learning models easier. They are using deep learning models today for image processing and language processing.
I think it is a fairly straightforward interface generally. It is an easy-to-use solution compared to SAS Enterprise Miner, for example. On the other hand, compared to some other products, maybe the UI could be enhanced. The visual interface could have something like the-drag-and-drop features which Alteryx already supports. Some of those additional features can make RapidMiner a better tool and maybe more competitive or advanced.
When I started using RapidMiner, I found it difficult to get it to read the metadata. I wanted to use, for example, a pivot table, and it did not have the variable or the attribute names in it. There were no values. It took a long while to figure out how to do that, although it tends to do it automatically nowadays. RapidMiner is not utterly intuitive for beginners. Sometimes people have trouble distinguishing between a file in their own file system and a repository entry, and they cannot find their data. This is an area where this solution could be improved. It would be helpful to have some tutorials on communicating with Python. I found it a bit difficult at times to figure out which particular variable, or attribute, is going where in Python. It is probably a simple thing to do but I haven't mastered it yet. I'd like them to do a video on that. There are a large number of videos that are usually well-produced, but I don't think that they have one on that. Essentially, I would like to see how to communicate from RapidMiner to Python and from Python to RapidMiner. One of the things I do a lot of is looking at questionnaires where people have used Likert-type scales. I don't recommend Likert-type scales, but if they're properly produced, which is a lot of hard work and it's not usually done, they're really powerful and you can do things like normalizing holes on the Likert scale. That's not the same as normalizing your data in RapidMiner. So, I would want to get results with these Likert scales, pass it through RapidMiner, do a normalization and pass back both the raw scores and the normalized scores and put in some rules, which will say if it's high on the raw score and on the normalized score and low on the standard deviation, then you can trust it.
The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator.
I think it's a great product but confusing in some way with regard to the user interface and integration with other tools. An improvement would be the addition of some buttons which would be useful because I'm sometimes unsure why I need to use something or what is its purpose. I would say the same goes for additional features, the addition of buttons would be helpful. The product is better than other software that I use.
RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models.
I would like to see all users have access to all of the deep learning models, and that they can be used easily. RapidMiner loads very slowly, which is something that should be improved.
The price of this solution should be improved.