InetSoft Technologies headquartered in Piscataway offers their Style Intelligence visualization and analytics solution, delivering mashup driven dashboards & reports with machine learning Intelligence.
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JMP
Score 9.2 out of 10
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JMP® is statistical analysis software with capabilities that span from data access to advanced statistical techniques, with click of a button sharing. The software is interactive and visual, and statistically deep enough to allow users to see and explore data.
We found that InetSoft Style Intelligence was easier to use and provided more enhanced functionality and more visibility in terms of visualizing information and data. During the proof of concept trials, we found that the dashboards were easier to create and the overall usage …
InetSoft is a more cost-effective option that offers the same functionality, features, and usability. It is a great option, especially for SMEs. It also has top-notch customer service/support which is a key factor in selecting any agency or tool. I recommend using InetSoft …
Much better than Excel for deep data dives, but also much steeper learning curve. And the cost is significantly higher - Excel is provided by default, but we have to request a JMP license each year.
It is great because it has UI menus but it costs money whereas the other programs are free. That makes it ideal for beginners but I think that RStudio and Python are going to make someone a lot more marketable for future opportunities since most companies won't pay for the …
JMP is superior to the MS Excel product in its graphical presentation and graphical exploration platforms. It has minor deficiencies in the lack of a 'goal seek' formula (although one can sort of get to this using the simulation platforms in some of the higher level ML …
Compared to other, similar programs, JMP is outstanding in ease of use and ability to be used by almost anyone across an organization. It is more fluid, user friendly, and, most importantly, requires no coding experience. The only two areas where it is not as good as …
JMP is more user-friendly, in my opinion, as it doesn't require any coding or searching for hours into cryptic folders for the analysis you want to perform. It is also very good for recording large data sets. Moreover, it is compatible with Microsoft Excel.
For me, JMP is the best and easy way to run regressions. I wouldn't use it for other more advanced models. I decided to use it because we got it for free since we are technically an academic institution.
I have only used STATA as a statistical package, and they are completely different tools. JMP has a much better layout and ease of use, but may not be as powerful as STATA for advanced processes. Overall speed and ease of use makes it like a combination of ms excel and stata …
We actually use both JMP and IBM SPSS, but I think JMP's complexity lends itself to more in-depth statistical analyses. SPSS is designed for that as well, but we tend to use it more for quicker analyses, and we have found that JMP is far more powerful.
Verified User
Anonymous
Chose JMP
Minitab, MODE. JMP is more user-friendly, interactive, and visual, with larger variety of analysis and tools. DOE platform itself is superior to any other software, instead of fitting the problem to classical design, the design is fitted to any problem and constraints.
MS Excel is good for manipulating data and providing flexible data arrays, but has serious deficiencies in its graphical displays and analytic capabilities. This is where JMP has its greatest advantages...see some of my previous comments, but I see these software applications …
Verified User
Anonymous
Chose JMP
Compared to: MSExcel - Useful from engineering data analysis perspective Matlab - cost/ expensive licensing
I much prefer the ability to code my programs which is the main method used in both SAS and R. These software choices allow for quicker, more efficient, and more advanced analysis techniques. The one area that JMP is above these is in graphics and visual displays of data. JMP …
Quality and Reliability Engineering Intern, Manufacturing, Intel
Chose JMP
Well, JMP is excellent for statistical analysis. So, this product it is well used for statistical analysis and data analytics.
Verified User
Anonymous
Chose JMP
As I stated before, you can use Excel to do many similar things to JMP; you can even use SAS to create graphs without having to do any sort of exporting. If you use SAS, however, you know these graphs are hideous, and sometimes using an Excel graphs makes you look like you are …
I heard good things from colleagues who have used JMP. We did not get too far down the SPSS route before we decided to go with JMP because of price and perceived benefit from my colleague's advice.
JMP simply excels against its competitors and the best way we know that is from our clients who have switched from other products. They recognize that their analytical capabilities are much higher with JMP then with whatever tools they used in the past. The ability to integrate …
Verified User
Anonymous
Chose JMP
JMP is more powerful in terms of data graphing, correlation analysis, profiler capability, and DOE functionality.
JMP is better with visual data representation, and as a general statistics exploration package. Technical needs like Design of Experiments are just easier to do in JMP
MS Excel with AnalysisToolPak provides a home-grown solution, but requires a high degree of upkeep and is difficult to hand off. Minitab is the closes competitor, but JMP is better suited to the production environment, roughly equivalent in price, and has superior support.
In my experience, InetSoft has been very useful in consolidating, visualizing, and democratizing data. It has helped me in many projects, especially given my role as a growth analytics and market insights specialist. Can't really think of scenarios where it is less appropriate.
Many organizations have seen their analytical capabilities, and the results from them, plateau. Of these, we've observed, that most of them didn't appreciate that they could do (even) better. These companies should definitely consider JMP. Any company that is research-based can benefit from accelerating their research, learning more in less time, effort and cost, with JMP's tools. Basically, any organization that is hungry enough for improvement to seek out better ways is suitable for JMP. Those who are happy with their current performance are not likely to consider the changes, though they were not major impediments by our clients, required.
I've mentioned this earlier, but the licensing agreements are very prohibitive. I work with a company where my role has become less and less doing my own analytics and more and more trying to help other people in that role. As we are bringing more people "up to speed" it's hard to justify licenses for 2-3 people when they aren't full time, Six Sigma black belts just looking at stats all day. A floating license option would make this a no-brainer, since these people could continue their other work and add JMP usage as they grow their skills, but this is not something JMP/SAS has offered.
The GUI interface makes it easier to generate plots and find statistics without having to write code. The JSL scripting is a bit of a steep learning curve but does give you more ability to customize your analysis. Overall, I would recommend JMP as a good product for overall usability.
The helpful tips are great for new users. I am always able to find solutions to a tool I am working with through the hep section. And my area has a users group that meets each quarter to share ideas and view upcoming JMP revisions.
We found that InetSoft Style Intelligence was easier to use and provided more enhanced functionality and more visibility in terms of visualizing information and data. During the proof of concept trials, we found that the dashboards were easier to create and the overall usage and the GUI were simpler, cleaner, more user friendly. Our product license costs were also cheaper.
We actually use both JMP and IBM SPSS, but I think JMP's complexity lends itself to more in-depth statistical analyses. SPSS is designed for that as well, but we tend to use it more for quicker analyses, and we have found that JMP is far more powerful.
JMP has resulted in literally millions of dollars in ROI due to identification of correctable errors.
Use of JMP control charts JMP has greatly simplified and improved interpretation of Lean, FMEA, and PDSA type analyses.
Use of JMP has enable the testing and subsequent selection of 'best practices' saving uncounted hours in false starts based on 'collective experience'.
The down side is that JMP is not a 'magic box', one still has to take care in applying the tools properly. Moreover, time-consuming approaches using JMP may still be the 'order of the day', because the service (even power user) is unaware of significant shortcuts available for free on the JMP community website.