JMP Pro offers all the capabilities of JMP, plus advanced features for more sophisticated analysis including predictive modeling and cross-validation techniques.
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KNIME Analytics Platform
Score 8.3 out of 10
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KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.
JMP Pro is perfectly suited for statistical analysis but users should have some statistical knowledge before using it since there may be some terms/functions in the software that are not widely used in other fields. No prior coding experience is needed to use JMP Pro. However, most people doing data processing would prefer to code their analysis.
KNIME Analytics Platform is excellent for people who are finding Excel frustrating, this can be due to errors creeping in due to manual changes or simply that there are too many calculations which causes the system to slow down and crash. This is especially true for regular reporting where a KNIME Analytics Platform workflow can pull in the most recent data, process it and provide the necessary output in one click. I find KNIME Analytics Platform especially useful when talking with audiences who are intimidated by code. KNIME Analytics Platform allows us to discuss exactly how data is processed and an analysis takes place at an abstracted level where non-technical users are happy to think and communicate which is often essential when they are subject matter experts whom you need for guidance. For experienced programmers KNIME Analytics Platform is a double-edged sword. Often programmers wish to write their own code because they are more efficient working that way and are constrained by having to think and implement work in nodes. However, those constraints forcing development in a "KNIME way" are useful when working in teams and for maintenance compared to some programmers' idiosyncratic styles.
I think the most awesome thing about JMP Pro is the Profiler component. The Profiler component makes sharing analyses interactive on the web using interactive HTML5. The Profiler makes showing the impact of interaction effects so easy. It's the best statistical software feature I think I've ever come across.
JMP Pro does dashboards well. It is relatively straight-forward to create four pane dashboards that automatically update. I think it's nice.
I think JMP Pro graphics are a massive improvement when compared to the graphics produced by its parent company - SAS. JMP Pro's features are vast, and easy to use and understand.
We are happy with Knime product and their support. Knime AP is versatile product and even can execute Python scripts if needed. It also supports R execution as well; however, it is not being used at our end
KNIME Analytics Platform offers a great tradeoff between intuitiveness and simplicity of the user interface and almost limitless flexibility. There are tools that are even easier to adopt by someone new to analytics, but none that would provide the scalability of KNIME when the user skills and application complexity grows
KNIME's HQ is in Europe, which makes it hard for US companies to get customer service in time and on time. Their customer service also takes on average 1 to 2 weeks to follow up with your request. KNIME's documentation is also helpful but it does not provide you all the answers you need some of the time.
KNIME Analytics Platform is easy to install on any Windows, Mac or Linux machine. The KNIME Server product that is currently being replaced by the KNIME Business Hub comes as multiple layers of software and it took us some time to set up the system right for stability. This was made harder by KNIME staff's deeper expertise in setting up the Server in Linux rather than Windows environment. The KNIME Business Hub promises to have a simpler architecture, although currently there is no visibility of a Windows version of the product.
The intuitive interface JMP Pro offers is more interactive than R studio, but since coding is not required in JMP Pro, programming analysis in R studio is more convenient in some aspects. JMP Pro is able to quickly analyze multiple variables and produce reasonable outputs and models, which is valuable for users doing data analysis.
Having used both the Alteryx and [KNIME Analytics] I can definitely feel the ease of using the software of Alteryx. The [KNIME Analytics] on the other hand isn't that great but is 90% of what Alteryx can do along with how much ease it can do. Having said that, the 90% functionality and UI at no cost would be enough for me to quit using Alteryx and move towards [KNIME Analytics].
The overall ROI for JMP Pro was positive because of the Profiler option. This makes communicating the results of regressions as easy and complex as needed. It's such an awesome feature, I wonder why it wasn't offered before.
If JMP Pro didn't have the Profiler feature, I think I would still recommend using JMP Pro, but the recommendation is not a slam dunk. The software has its own programming language, which is not well-known and requires effort to debug.
JMP Pro's dashboards are well-built, and provide a positive ROI from the perspective of creating real-time, interactive reporting. It's very nice for this feature.
It is suited for data mining or machine learning work but If we're looking for advanced stat methods such as mixed effects linear/logistics models, that needs to be run through an R node.
Thinking of our peers with an advanced visualization techniques requirement, it is a lagging product.
