An incredibly comprehensive and powerful data analytics platform that is somehow free
Overall Satisfaction with KNIME Analytics Platform
The KNIME Analytics Platform provides a comprehensive set of tools for addressing the data manipulation and data science issues we encounter. Internally we use it for training new data scientists, building awareness of the data science workflow and data manipulation with non-technical staff. We also use it on our own data projects. The no-code environment allows us to focus on the methodology and intent of analyses with novice users without them encountering errors in syntax as they would if they were learning to code at the same time. However, the R and Python nodes allow experienced data scientists to work in their preferred language as well as allowing us to scaffold the learning of new data scientists in those languages when it becomes advantageous. We find non-technical clients will engage with the visual node structure much more than code, which helps us get to a solution more quickly. We can deliver stand-alone solutions to clients with confidence that we are not tying them into an expensive vendor relationship. Clients value that they can give access to all of their users at no licencing cost. Where collaboration and automation is required, KNIME Analytics Platform offer an extremely competitive server solution.
Pros
- Connectivity to an array of data sources and joining the data
- Rapid prototyping across data science use cases
- Making data science explainable to non-experts
- Democratising data - KNIME Analytics Platform allows everyone access to powerful analysis techniques
- Providing simple access to powerful external data science tools such as H2O and hyperscalers
Cons
- The previous UI of KNIME Analytics Platform provided easy access to a wide range of examples which is an extremely valuable resource for understanding how to break down a problem in KNIME Analytics Platform and provide accelerated delivery for similar use cases. Access to these resources doesn't seem possible at the moment in the new UI, but I believe it is being actively worked on. The examples are still available in the platform, but presently you need to switch back to the old UI.
- KNIME Analytics Platform is free and our investment in training time has been paid back many times over when using the software for rapid prototyping and implementing our own analysis
- On one occasion we deployed KNIME Analytics Platform and Python with a client. Due to their secure environment, it was prohibitively expensive in time and capital to add Python packages to account for additional requirements as the project progressed and we switched entirely to KNIME Analytics Platform due it its comprehensive set of features. Without KNIME Analytics Platform the project would have been halted and resulted in a loss of >£40k in revenue.
There are two aspects which put KNIME Analytics Platform ahead of other products. Firstly the fact that KNIME Analytics Platform comes at no cost and no restrictions on its use is an instant winner for any organisation wanting to democratise their data. It means that a client is free to install it on as many machines as they wish without worrying about costs, the number of seats required or payment models or procurement negotiation. It also means that we are not building costs into our clients business.
Secondly, KNIME Analytics Platform has a very comprehensive set of tools for importing/exporting data, data manipulation and data science. Some products offer analytics packages on top of their base offering at additional cost and they are still not as comprehensive as what you get with KNIME Analytics Platform for free. For some types of analysis you may require to download additional packages with KNIME Analytics Platform, but its invariably at no cost, those packages are kept out of the main download to keep the size down. Due to the easy integration with R and Python, I view KNIME Analytics Platform as also having the capabilities of those languages too. This has helped me in the past with seamlessly importing a rare filetype and using very specific models not directly available in KNIME Analytics Platform.
Secondly, KNIME Analytics Platform has a very comprehensive set of tools for importing/exporting data, data manipulation and data science. Some products offer analytics packages on top of their base offering at additional cost and they are still not as comprehensive as what you get with KNIME Analytics Platform for free. For some types of analysis you may require to download additional packages with KNIME Analytics Platform, but its invariably at no cost, those packages are kept out of the main download to keep the size down. Due to the easy integration with R and Python, I view KNIME Analytics Platform as also having the capabilities of those languages too. This has helped me in the past with seamlessly importing a rare filetype and using very specific models not directly available in KNIME Analytics Platform.
Do you think KNIME Analytics Platform delivers good value for the price?
Yes
Are you happy with KNIME Analytics Platform's feature set?
Yes
Did KNIME Analytics Platform live up to sales and marketing promises?
Yes
Did implementation of KNIME Analytics Platform go as expected?
Yes
Would you buy KNIME Analytics Platform again?
Yes
KNIME Analytics Platform Feature Ratings
Evaluating KNIME Analytics Platform and Competitors
- Scalability
- Integration with Other Systems
- Ease of Use
- Other
Price. It's free, which meant no headaches with Procurement or licensing, anyone can download it, install it and use it without restriction.
I wouldn't change it. We talked to a variety of organisations working in the space, engaged in demos, tutorials and conducted comparisons on price and capability. KNIME Analytics Platform did not win out in every category, but it was the clear overall winner of our selection process and we have no regrets in making it our go-to no-code solution.
Using KNIME Analytics Platform
Pros | Cons |
---|---|
Like to use Relatively simple Easy to use Technical support not required Well integrated Consistent Quick to learn Convenient Feel confident using Familiar | None |
- Rapid prototyping
- Comparing model performance
- Connecting to data
- The concept of "flow variables" was a little difficult to grasp
- Regex is a bit limited so I often choose to use an R or Python node, so it's only a minor inconvenience.
- Building reports was a bit difficult in the past, but it's not something I've ever needed for a project and might have changed since I last tried.
Comments
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