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.
$1,320
per year per user
SAS Viya
Score 6.8 out of 10
N/A
An end-to-end platform for AI, data science, and analytics, used for modeling, as well as management and deployment of AI models.
N/A
Pricing
JMP
SAS Viya
Editions & Modules
JMP
$1320
per year per user
No answers on this topic
Offerings
Pricing Offerings
JMP
SAS Viya
Free Trial
Yes
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Bulk discounts available.
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More Pricing Information
Community Pulse
JMP
SAS Viya
Considered Both Products
JMP
Verified User
Anonymous
Chose JMP
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.
SAS is just as good as these tools but is pricier. I like that it handles data visualization and modeling together in one platform that's a novel mechanism that is fairly rare. Also, it's forecasting capabilities are nicely integrated with the functionality overall which makes …
We had major use of SAS in forecasting where it doesn't require high level of coding knowledge and which has highly efficient models built in which can give good results on forecasts without lot of manual intervention. This tool was designed specifically for forecasting and …
SAS is faster then both SPSS and STATA. SAS also has better models and graphs when comparing the three softwares. However, STATA and SPSS are more user friendly. It is easy to use SPSS and STATA, because a lot of it is point-click. SAS requires some training to be able to use …
Director, Application Architecture and Programming
Chose SAS Viya
SAS has a much superior and comprehensive data preparation capability with a clear approach on how to handle and scale for a large amount of data and users. However, it can be more expensive to implement.
R is of course much cheaper (free) than SAS Analytics, and it can do everything SAS Analytics can do and more. It is a much more technical tool than SAS Analytics, which is why some people prefer SAS Analytics.
SAS was the incumbent tool, and what the team knew. We did look into using Revolution Analytics enterprise version of R, but the learning curve on that caused us to stick with SAS. In my current position, I've opted for WPS over SAS. I can still leverage my SAS experience, but …
SAS allows the user a wider range of capabilities to cleanse and manipulate the data. Not only can the data be pulled directly into SAS, but before it is finalized it can be transposed, graphed, or altered in any way imaginable which puts it a step above the Business Objects …
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.
We piloted SAS AA at my organization to see how well it compares with other free software tools such as RStudio and Anaconda. So far what we saw was very impressive especially with the visual display but was a little out of our price range. It would be useful in analyzing population health metrics combined with financial data.
SAS Analytics does not have very good graphic capabilities. Their advanced graphics packages are expensive, and still not very appealing or intuitive to customize.
SAS Analytics is not as up-to-date when it comes to advanced analytical techniques as R or other open-source analytics packages.
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.
Not only does SAS become easier to use as the user gets more familiar with its capabilities, but the customer service is excellent. Any issues with SAS and their technical team is either contacting the user via email, chat, text, WebEx, or phone. They have power users that have years of experience with SAS there to help with any issue.
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.
If SAS Enterprise Guide is utilized any beginning user will be able to shorten the learning curve. This is allow the user a plethora of basic capabilities until they can utilize coding to expand their needs in manipulating and presenting data. SAS is also dedicated to expanding this environment so it is ever growing.
SAS probably has the most market saturation out of all of the analytics software worldwide. They are in every industry and they are knowledgable about every industry. They are always available to take questions, solve issues, and discuss a company's needs. A company that buys SAS software has a dedicated representative that is there for all of their needs.
Although nothing is perfect, SAS is almost there. The software can handle billions of rows of data without a glitch and runs at a quick pace regardless of what the user wants to perform. SAS products are made to handle data so performance is of their utmost important. The software is created to run things as efficiently as SAS software can to maximize performance.
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.
SAS is generally known for good support that's one of the main reasons to justify the cost of having SAS licenses within our organization is knowing that customer support is just a quick phone call away. I've usually had good experiences with the SAS customer support team it's one of the ways in which the company stands out in my view.
SAS has regional and national conferences that are dedicated to expanding users' knowledge of the software and showing them what changes and additions they are making to the software. There are user groups in most of the major cities that also provide multi-day seminars that focus on specific topics for education. If online training isn't the best way for the user, there is ample in-person training available.
There are online videos, live classes, and resource material which makes training very easy to access. However, nothing is circumstantial so applying your training can get tricky if the user is performing complex tasks. When purchasing software, SAS will also allocate education credits so the user(s) can access classes and material online to help expand their knowledge.
Ask as many questions you can before the install to understand the process. Since a third party does the installation your company is sort of a passanger and it is easy to get lost in the process. It also helps to have all users and IT support involved in the install to help increase the knowledge as to how SAS runs and what it needs to perform correctly.
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.
SAS is faster then both SPSS and STATA. SAS also has better models and graphs when comparing the three softwares. However, STATA and SPSS are more user friendly. It is easy to use SPSS and STATA, because a lot of it is point-click. SAS requires some training to be able to use it as effectively as possible. SAS is better with large data sets, and it is easier to analyze many data points at the same time
It all depends on the type of SAS product the user has. Scaleability differs from product to product, and if the user has SAS Office Analytics the scaleability is quite robust. This software will satisfy the majority of the company's analytic needs for years to come. In addition, if SAS is not meeting the users needs the company can easily find SAS solutions that will.
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.