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
Tableau Desktop
Score 8.1 out of 10
N/A
Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
$75
per month per user
Pricing
JMP
Tableau Desktop
Editions & Modules
JMP
$1320
per year per user
Tableau
$75
per month per user
Tableau Enterprise
$115
per month per user
Offerings
Pricing Offerings
JMP
Tableau Desktop
Free Trial
Yes
No
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.
All pricing plans are billed annually.
More Pricing Information
Community Pulse
JMP
Tableau Desktop
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.
Both power bi and Tableau Desktop has its own pros and cons. Microsoft power bi is best to work with Microsoft products. however for fast connection with diverse range of integration with data sources Tableau Desktop is best. if you are cost sensitive power bi is best option …
Tableau is more flexible than these - I liked Qlikview old version a lot but have not used the Qlik Sense etc new ones. Tableau user logic is harder to understand than Looker Studio. However it's more trust worthy. Connecting internet sources to Tableau Desktop is much harder. …
Tableau Desktop is older and just better overall. It has more capabilities and is more useful to have. I don't think you could have Alteryx as a standalone product like you can with Tableau Desktop. You'd want another bi tool.
Tableau Desktop has a more easy to use drag and drop interface and is easier to learn. It also allows greater customization of charts than Power BI. However, Tableau Desktop costs more than Power BI which is bundled into our Microsoft contract at no additional charge. Power BI …
The visualizations are far and away more powerful and it is more user friendly than Power BI. It would take 3-4 times as long to create the types of reports in Excel that I can create in Tableau Desktop and there are a slew of ways I can present the data in Tableau Desktop that …
It has a better user interface compared to Microsoft Power BI. The Tableau integration process is quite simple and clear with the third-party application whereas Power BI is not easily integrated with other tools and requires a complex process to follow for integration. DAX …
When it comes to pricing, Tableau is kinda expensive but worth it as it has more features, not just features but really useful features that make our work easier especially as a project manager I need to pull up data almost every day in our meetings, and I find Tableau useful …
Tableau can create visually attractive customizable dashboards than can quickly by drag-drop while in power bi we can create simple dashboard. Power bi support lesser data source while in Tableau there is a lot of options When we talk about data handling tableau is a clear …
Tableau Desktop is clearly one of the best in the business. It has incredible capabilities, and many features are extremely useful. The intuitiveness of the dashboards and the graphical nature of the visualizations are widely used features and super helpful. One of the other …
Tableau Desktop provides some state of the art feature and capabilities that are just awesome. Its support, online blog, and tutorials are better than its competitors. That was the best selling point for me.
With Tableau Desktop, it's easy to create a report in the
context quickly. It allows for the seamless management of the data sources,
which is convenient for the data users. Because it is simple to use, it is
It does have a lot of potential when using Microsoft other technologies - in integration/Embedded, Visuals and connectivity to data sources. Advanced analytics is also smooth when working on python/r scripts. Automated insights are better in Tableau/Alphaa AI. NLG/NLQ - …
For complex data visualization, Tableau Desktop shines. Even though it uses highly granular databases, it has a powerful engine that can process large amounts of data quickly and produce high-quality charts. It has the broadest range of APIs and is extremely simple. The …
We decided to use Tableau Desktop as that's fairly standard in the industry, it is being taught in college, and is widely known. Tableau Desktop is nice, but in my opinion, it is VERY expensive. Unless you are really making money off of decisions, then your ROI is going to be …
Using Tableau Desktop, we have found it the most actionable and user-friendly application ever. It has the broadest range of APIs and is exceptionally user-friendly. It can handle a large amount of data and produce smooth charts quickly. For data geeks, this is the ideal stack.
When compared to Power BI, Tableau has a more flexible deployment. You can install the desktop version without having to install the SQL server. Tableau got you covered end-to-end — from collaboration, analytics, content discovery, data prep & access, down to deployment. …
Tableau Desktop is preferred over other BI software because it allows for more data visualization, storytelling, and dashboards. Microsoft Power BI may be a better option if you need to perform data modeling, however. Tableau Desktop is an excellent tool for nearly all other …
We preferred Tableau over Power BI due to its user-friendly interface and interactive GUI. Since we work with large datasets, we observed that Power BI can deal with only a limited amount of data when compared to Tableau which creates complex visualizations in a time-efficient …
Tableau Desktop is the most user-friendly and actionable application we have used in comparison to others. It has the best API connection potential along with easy start-up. They seem to always be updating the platform to solve newer problems which help keep my company up to …
We also use Power BI for small projects and teams that can't afford to pay for Tableau licenses. Tableau has more features and is more robust compared to Power BI. They also provide better and faster support compared to Microsoft. It is the standard visualization tool, but …
For databases or types of data that have high granularity and details, Tableau Desktop is better to plot and help visualize every detailed behavior with a great performance. It's engine can process a massive amount of data and generate a smooth chart without spending too much …
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.
The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).
The Visualizations graphics are really good and the color options help in designing attractive charts. They help to convey more information and can be made interactive.
You can add filters with offer you to plug and play with values and understand different outcomes.
You can drag and drop options while creating charts and dashboards. also it is a very fluid layout.
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.
Because right now its the best option out there (disclosure: I haven't used Qlikview or some of the other direct competitors of Tableau). The big investment is in Tableau Server not desktop. For the cost of the license of Tableau desktop, its a pretty good deal. You can hook it up to pretty much any data source easily. You can easily share the visualizations with your team/colleagues easily. Tableau Desktop is generally easy to use for business users. But the more advanced stuff is better suited for a analyst or someone with a IT/CS background.
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.
Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
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.
The Tableau Desktop's support team has been very helpful and tend to response very quickly. After all you have paid very premium price for the product and it goes to the services. This makes using the tool much easier for these who doesn't have such experience to get help quickly.
It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems
Time needs to be spent ahead of implementation to make sure data sources are set up and ready. Consultants need to understand the data sources and the goals before setting foot on-site. Installation is easy, learning to use it takes time. The training resources available are great.
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.
Tableau Desktop is clearly one of the best in the business. It has incredible capabilities, and many features are extremely useful. The intuitiveness of the dashboards and the graphical nature of the visualizations are widely used features and super helpful. One of the other benefits is that both programmers and non-programmers can equally explore and create their own opportunities, and seamless integration is possible.
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.
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.