KNIME Business Hub Reviews

I use KNIME for analysis-related purposes. I am currently in the process of developing some models for analysis.

The most valuable feature of the solution stems from the fact that it is a user-friendly tool where a person doesn't have to get involved with codes since you just need to drag the nodes to create your model, which is a very easy process for me.

The most difficult part of the solution revolves around its areas concerning machine learning and deep learning. The aforementioned area can be considered for improvement.

I have been using KNIME since 2019. I am an end user of the solution.

It is a stable solution.

It is a scalable solution.

I am the only user of the solution in my company. I do provide training to other employees in my company on how to use KNIME.

I have experience with Excel, and I faced some limitations since my company had loads of data to analyze. Considering that my company had loads of data to analyze, I would say I find KNIME to be very useful.

My company has some problems related to the solution's updates. I don't know if there are some restrictions from my organization because of which I cannot update or install some extensions.

The solution can be deployed in a few minutes.

The solution is currently deployed only on my personal computer, which I use in my company.

Only one person or an IT administrator is required to take care of the installation phase of the product.

KNIME is a cheap product. I currently use KNIME's open-source version.

I have experience with Python. Compared to Python, KNIME is better because of the user-friendliness it provides. With KNIME, you don't have to get involved with codes. KNIME provides nodes, making it a very easy tool to use.

I have not received any response from my company, though I had proposed to my organization to buy KNIME so that we can use it on the servers since, right now, it is like a standalone tool used on my personal computer only. I am just a basic and not an advanced user of KNIME. I find KNIME to be a very useful tool.

Speaking about the maintenance phase of the product, I would like to say that I cannot update the solution. If a new version is released, I cannot update the product. I always have to request my organization and the IT team to download and install the product's new version for me.

I recommend others to use KNIME. I have recommended KNIME to my colleagues.

I rate the overall solution an eight out of ten.

We have been using the most recent version. It's version 4.6.

10 August 2023 - It has now been upgraded to 5.0 and is, if anything, even more impressive, especially in its ability to use Python and its libraries.

Knime seems to keep getting better. Their open-source model seems to be working. The addition of AI both to help in the building of workflows and as a facility within a workflow once it is up and running seems to add a dimension. At the moment, though, the system is so rich and fully featured that I have explored only the surface of the new version (5.4).

To date, all my needs have been met by earlier versions of Knime. I am, though, confident that should I need to start using version 5.4, the process will be smooth, and the new functionality fit for purpose. Upgrades to Knime have always worked like that in the past and I would expect them to do so in the future.

I used to be a Pascal programmer, and then I did a bit of Python. It does many of the things that I would've had to do in code, but does so without using code. I don't think it does everything, but it does most of what I need to do.

It can read many different file formats. It can very easily tidy up your data, deleting blank rows, and deleting rows where certain columns are missing. It allows you to make lots of changes internally, which you do using JavaScript to put in the conditional.

For example, I have one data set whereby all of the data is encoded and there was one variable called opinion or something like that and it had codes for what the topic was, which was being discussed, whether it was positive or negative, whether it was strongly worded or weakly worded, and so many other things like that.

I had to transfer those into columns, like sentiment, the strength of sentiments, topic being discussed. I had to split it up into columns, and I could do that very easily, like simple JavaScript, in their column expressions.

It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured.

They are also very careful with things like lab variants and issued variants because they have some labs that develop nodes, and new chunks of code which are represented as an icon. They make it very clear that those lab ones are not fully tested, and they're very glad to get comments back if you have problems.

I haven't had that difficulty myself. They seem to be aware that they have the community there as their testing base, and they seem not to be embarrassed about that. They will tell you when they go wrong and try to put it right.

So far, I haven't had problems with it, so I haven't really thought about room for improvement. It's so much better than many other things. It's useful in that you can at least get people who are pretty averse to programming to start thinking about putting something into a program of any kind, because they can see what's happening.

It's visual. It's codeless. For some purposes, I'd want to add Python or R, but I haven't had to do that so far, so I haven't seen the shortcomings of it. There must be some. All software has shortcomings, but I haven't recognized any myself.

Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself.

I use both Thurstone scales and magnitude ratio scales quite a bit, and they're very powerful. But I've always had to do all the analysis myself in some simple code. I don't think that's provided. You could probably include it in KNIME, but I haven't tried to do it.

If it just said, "Analyze scales," and you'd choose which sort of scale you want to analyze and it gave you the options of normalizing or reversing or whatever it happens to be, that would be helpful. There are lots of simple functions that you want to apply to scales, which would be useful in any software, including KNIME.

I have been using this solution for about a year, but most particularly in the last six months.

It's been remarkably stable, much more so than most software. They have an active community forum. Problems seem to get fixed pretty quickly. I haven't had problems, but other people do report problems. So, there must be problems there, I just haven't had any.

On the very rare occasions that I have to seek advice, I just post it to the forum and someone will offer advice.

Positive

Compared to RapidMiner, at the moment I would go for KNIME, but that's largely because I haven't used RapidMiner much for the last year. It may have improved enormously since then. It was a very good package. They do much the same thing.

I'm more familiar with KNIME, so I would be able to talk more about it, whereas for RapidMiner, I was very enthusiastic when I used it. KNIME is a bit cheaper in a sense.

In RapidMiner, you can have up to 10,000 rows of data free of charge. For many things that I do, 10,000 rows of data is enough. I use quite a few UK government surveys, and I get the raw data from the UK Data Archive. They're often of the order of 10,000, 8,000. So, under 10,000 rows. I could use it free of charge.

I just downloaded it and then ran it. The process really was that simple. If I need one of the extensions (e.g. text mining), the process is just as simple.

We implemented the solution in-house.

I have not formally calculated it, but it must be substantial.

With KNIME, you can use the desktop version free of charge as much as you like. I've yet to hit its limits. If I did, I'd have to go to the server version, and for that you have to pay. Fortunately, I don't have to at the moment.

I would rate this solution an eight out of ten. 

I'm unwilling to give anything a ten because everything can be improved. But it's been very useful so far to me and has saved me many hours of work. I could have written it all in Python if necessary, but it would have taken me weeks for what would be a few days of work.

My advice is to just download it and use it. The documentation is pretty good. There are many good videos online for it. If you go to YouTube, you can get pages and pages of KNIME tutorials. They're pretty clear, and they are produced by people who've used it. It's not just company advertising, as far as I can see.

It's mostly data preprocessing, handling, and processing (ETL) processes, as well as expanding the transport load. 

Additionally, we also work on various machine learning tasks, such as regression models and other small topics related to machine learning.

I've tried to utilize KNIME to the fullest extent possible to replace Excel. Our company has been heavily reliant on Excel for generating reports and performing data transformations. With KNIME, I've been able to combine data from Excel, SQL Server, and various other resources efficiently.

There are a few aspects that I am not entirely satisfied with. For instance, when integrating KNIME with our SAP system ERP and HANA, it's not as straightforward as expected. We need to find alternative connectors like the Teradata connector, which adds complexity.

So far, I've had some problems integrating KNIME with other solutions. Thus, it could be an area of improvement. 

We have been using KNIME for two years.

Overall, the product has been stable. It has efficiently handled the tasks we have encountered so far.

There are two end-users using KNIME in our organization. Because we are still beginners, we are only using it to learn how it works and get a better understanding of the system. We are not yet certain if we will use it extensively for all topics.

The initial setup was easy. 

I deployed the solution myself. 

We use the free version only. 

We are working with KNIME on some small projects, but we are also looking for an alternative solution to explore.

Overall, I would rate KNIME a seven out of ten because we faced a problem with the integration with other products, like SAP.

I'm a professor, and I learned about KNIME from a data science course. I use KNIME for data visualization, manipulation, and generation.

What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node.

It's also helpful to learn more about the different concepts in KNIME, such as data mining, neural networks, and other visualization nodes for generation. You can gain a lot of insight from the tool as a data scientist.

Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing. This is an area for improvement because not all nodes appear in the 64-bit system. In other systems, you get to use all nodes or features. It should be uniform in all systems, though I have no idea if it's a software problem or a corruption in the system that's in the college lab. At home, I can see and access the image reader node, but in school, that node is missing.

What I want to be added to KNIME is the feature of extracting data from social media platforms, whether structured or unstructured and for that data to be automatically converted into a CSV file that I can use. I want a data cleaning and collection process from KNIME that works for social media platforms because datasets in social media can serve as business intelligence or can aid businesses. Social media is the trend nowadays, so I want a KNIME node to analyze data from social media platforms.

I'd been using KNIME for three months now.

In my three months of using KNIME, its stability has been okay, but I want to explore the tool more. Stability-wise, it's a seven out of ten. When the network is stable, then KNIME is okay to use.

KNIME is a scalable product, so I'm rating it as nine in terms of scalability.

I've not used any other tool besides KNIME, but I'm planning to try RapidMiner, which I've not yet installed.

KNIME was easy to set up, so it's a ten out of ten, setup-wise.

KNIME is an open-source tool, so it's free to use.

At the moment, only ten students use KNIME. The course just started.

In my three months of experience with KNIME, it's an eight out of ten.

We are using KNIME for price prediction, privacy missions, the commander model, ETL, and a couple of algorithms we've developed.

One of the greatest advantages of KNIME is that it can be used by those without any coding experience. Even those with no coding background can use it. 

KNIME can be used by people without coding experience. It can be used by people who don't have an IT background and don't have coding knowledge. This is different from Python or R, which require coding experience to use.

When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area.

I have been using KNIME for approximately one month.

I'm not sure if it is stable, we'll have to see how KNIME performs with larger amounts of data, as I have heard it is not very reliable. With smaller data sets, however, it seems to be stable.

We will use this solution more in the future when we do not need people with coding experience.

We have two people who are using this solution in my organization.

I have not used the support from KNIME.

I used the open-source package and started experimenting with it in Python, R, and KNIME. For KNIME, I had to go through the KNIME forum for troubleshooting. I didn't get a response for any of the issues I encountered on the KNIME forum. As for other open-source languages, I haven't received a response for any of the issues I faced either.

The initial setup of KNIME is easy. It can be done with the interface within half an hour.

I had taken some online courses and read about KNIME, and I wanted to try out a drag-and-drop software. I was interested in evaluating KNIME, and this is why I am using it.

My advice to those who are new to data science and don't have any coding experience would be to use KNIME, along with some other programming languages. KNIME is great for creating visualizations and dashboards, and I have advised a few of my colleagues to use it for their own projects.

I rate KNIME a seven out of ten.

We use the solution for data analytics and logic design.

The product is working fine with Oracle.

It is is written in Java. If they can output the Javascript, it will be much better. Also, it could be integrated with Visual Studio.

I have been using KNIME for three years.

20 users are using this solution. Scalability is quite easy, but handling many notes can become messy.

Most of the things is available in the community.

It's quite easy to setup.

I have a CSV reader. When I reset that CS reader, and It gave some error.

I have a CSV reader, and I encounter an error whenever I try to save. However, if I reset the CSV reader, I am able to save successfully. It’s a rare issue, but there's something wrong with the CSV reader. The error message doesn't provide a solution, only indicating a problem with the CSV reader.

I want to save the project but always face saving issues. If I reset the node, the saving works fine. The error message isn’t clear about what is wrong or how to fix it. I discovered on my own that resetting the CSV reader from green to yellow allows me to save the project. This issue is quite rare.

Last Friday, there was a widespread CrowdStrike issue, and I had to restart my computer. After restarting, I lost my entire project.

I recommend the solution.

Overall, I rate the solution a nine out of ten.

I encountered a problem that I managed to resolve effectively. I documented the issue in a paper and aimed to determine if the issue was due to normal network behavior or an anomaly. To investigate, I employed machine learning models and used the KNIME’s database. I gathered a significant amount of data and extensively applied machine learning models. Ultimately, I achieved improved data accuracy, especially in the context of network data.

I believe that some individuals may not be skilled programmers, and this is where the agenda comes in. It allows for a user-friendly approach where you can simply drag and drop elements to create your model, which is a convenient and effective idea.   

The pricing needs improvement. 

I have been using KNIME for the past six months.

It is stable solution.

It is scalable solution. 

The initial setup is straightforward.

It is expensive to procure the license.

I would rate the overall solution an eight out of ten. I would suggest this application to individuals involved in auditing. It's user-friendly and makes it easy to initiate model creation.

I am an intern. I am pursuing my master’s degree. I use this solution to propose a solution for accreditation review. I needed a tool to automate this task for my sources. This solution has helped me to do that.

The dynamic column name feature could be improved. When attempting to automate processes involving columns, such as with companies, it becomes difficult to achieve the same result when we make changes. So maybe it would be helpful to have a way to find similar column names automatically and execute a single approval, for instance.

In future releases, I can suggest having an API along with tools or services. This would allow for customization since the API is already available in other versions.

So, I suggest having an API for customization.

I have been using KNIME for six months.

I would rate the stability of KNIME a ten out of ten. 

I would rate the scalability of KNIME a six out of ten. 

I have used Alteryx. I prefer this solution over Alteryx because of the pricing point. KNIME is free and open source. 

The initial setup is easy. I will rate my experience with the initial setup a nine out of ten, where one means it's difficult to set up, while ten means it's very easy.

I deployed the solution myself. It took around one month to deploy it. 

KNIME is free and open source. I would rate the pricing model one out of ten, where one is low price, and ten is high price. 

It is a good tool and easy to learn. We do not need to know the codes before using the solution.

Overall, I would rate the solution a seven out of ten.