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
Spotfire
Score 8.1 out of 10
N/A
Spotfire, formerly known as TIBCO Spotfire, is a visual data science platform that combines visual analytics, data science, and data wrangling, so users can analyze data at-rest and at-scale to solve complex industry-specific problems.
N/A
Pricing
JMP
Spotfire
Editions & Modules
JMP
$1320
per year per user
No answers on this topic
Offerings
Pricing Offerings
JMP
Spotfire
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.
For Enterprise engagements, contact Spotfire directly for a custom price quote.
More Pricing Information
Community Pulse
JMP
Spotfire
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.
Spotfire has an extremely large and dynamic range of visual analysis tools that can be catered for most issues or projects to create a custom analytics dashboard when compared to other tools I've used. It's multitude of available database connections allow for most …
Spotfire is stronger than other tools to built complex metrics within the tool, without needs of etl updates and query changing. It has lots of useful visualizations to deep dive data and give interesting analysis to business users. Moreover, with some studies and tests, you …
Although Spotfire has a longer learning curve, it has proven to be more practical and impactful than Tableau. We had only evaluated other tools at a high level initially, and were surprised to hear the success stories of companies moving from Tableau to Spotfire. We have found …
Because of Spotfire's robust features and capabilities, I chose it as my
preferred software. Spotfire's greater overall performance and
scalability set it apart from other software solutions. It can handle
Spotfire is appropriate for every organization of any size because it can be a recipient of data for better decision-making. Being a robust development platform for creating reports and dashboards, creating a new Spotfire dashboard is relatively simple. Developers can create …
Spotfire is more suited for manufacturing industries with regards the huge data to process to make relevant decision that use big data for making decisions, besides this Spotfire supports more and excels at Availability & Scalability, Data Sources Connectivity and Deployment …
I choose Spotfire because of the following - custom visual using JavaScript - on the fly chart property update using iron python - easy report Deployment and update -easy to manage user access via so or ldap - best report data Extraction -mix data sources -custom data load …
Spotfire is significantly ahead of both products from an ETL and data ingestion capability. Spotfire also has substantially better visualizations than Power BI, and although the native visualizations aren't as flexible in Tableau, Spotfire enables users to create completely …
Spotfire's key strength les in extent of customization possible and it's inherent Data Analytics capabilities. With in-memory and in-database analysis capabilities, it comes out as a high performance and high efficiency BI solution. Adding to it, Spotfire integrates the …
Easy to use and is a very flexible tool. Great to have multiple services. Find it to be a trusted platform. The ability to add Iron Python scripts and include code snippets is very useful. Like the style of the created views.
I find both Microsoft Power BI and Spotfire very easy to use. I would rate them on par with each other. There isn’t much to differentiate them. Maybe the learning curve on Spotfire is a bit steeper than Microsoft Power BI.
Augmented AI with Spotfire is very useful for data virtualization. Since data visualization is a quick and very easy way to convey our information. This software makes it easier with its interactive way of presenting data in charts, graphs, and 3D forms.
It provides all tools along with in-built apps for analysis and generating reports, metrics, charts, and graphs. Comes with appropriate costing model at least for an average size organization
Spotfire is the best application for power users by virtue of its wide variety of visualizations, incorporated analytics, superior data canvas, and ability to integrate code such as R or Python. The learning curve is steeper and the menus are Windows 7 once you are past some …
The only other tool we use in my course is Tableau. Tableau is very popular regionally (Omaha, NE), runs locally on Mac and PC, is free for students and faculty, and has a web outlet for sharing. It also plays well with AWS. For these reasons, we use it as the primary …
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.
Spotfire was used to look at a large data set of an in process manufacturing step. The data visualization was set up to look at yield as a function of several inputs (chemical / equipment / operator). After only a short analysis it was immediately obvious that there was a 5% yield discrepancy based on the operator using the equipment. The operators were retrained and the yield gap was eliminated.
They should have a lower price point for users to access the analyst version who don't require advanced capabilities. For example, a lower price if users just need to do some basic slicing and dicing with their data and not have to the data science functionality (ie. K-means clustering, regression modeling, classification modeling, etc.).
Currently, you can't change the font type/color on the axis, which I'm sure will eventually be available in the future as they have a Spotfire Ideas portal that they're fairly responsive to and act on. I guess at the end of the day, it's about the data and what insights you get from it.
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.
It's a very powerful tool that allows for a myriad of customizations within the analysis files themselves, particularly with the custom expression functionality. There have been some great strides with the quality of the visualization options (which were not great to begin with) and I hope to see more improvements made as the product gets updated.
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.
Basic tasks like generating meaningful information from large sets of raw data are very easy. The next step of linking to multiple live data sources and linking those tables and performing on the fly analysis of the imported data is understandably more difficult.
Even though, it's a rather stable and predictable tool that's also fast, it does have some bugs and inconsistencies that shut down the system. Depending on the details, it could happen as often as 2-3 times a week, especially during the development period.
Generally, the Spotfire client runs with very good performance. There are factors that could affect performance, but normally has to do with loading large analysis files from the library if the database is located some distance away and your global network is not optimal. Once you have your data table(s) loaded in the client application, usually the application is quite good performance-wise.
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.
Support has been helpful with issues. Support seems to know their product and its capabilities. It would also seem that they have a good sense of the context of the problem; where we are going with this issue and what we want the end outcome to be.
The instructor was very in depth and provided relevant training to business users on how to create visualizations. They showed us how to alter settings and filter views, and provided resources for future questions. However, the instructor failed to cover data sources, connecting to data, etc. While it was helpful to see how users can use the data to create reports, they failed to properly instruct us on how to get the dataset in to begin with. We are still trying to figure out connections to certain databases (we have multiple different types).
The online training is good, provides a good base of knowledge. The video demonstrations were well-done and easy to follow along. Provided exercises are good as well, but I think there could be more challenging exercises. The training has also gone up in price significantly in the last 3 years (in USD, which hurts us even more in Canada), and I'm not sure it is worth the money it now costs (it is worth how much it cost 3 years ago, but not double that.)
The original architecture I created for our implementation had only a particular set of internal business units in mind. Over the years, Spotfire gained in popularity in our company and was being utilized across many more business units. Soon, its usage went beyond what the original architectural implementation could provide. We've since learned about how the product is used by the different teams and are currently in the middle of rolling out a new architecture. I suggest:
Have clearly defined service level agreements with all the teams that will use Spotfire. Your business intelligence group might only need availability during normal working hours, but your production support group might need 24/7 availability. If these groups share one Spotfire server, maintenance of that server might be a problem.
Know the different types of data you will be working with. One group might be working with "public" data while another group might work with sensitive data. Design your Library accordingly and with the proper permissions.
Know the roles of the users of Spotfire. Will there only be a small set of report writers or does everyone have write access to the Library?
ALWAYS add a timestamp prompt to your reports. You don't want multiple users opening a report that will try and pull down millions of rows of data to their local workstations. Another option, of course, is to just hard code a time range in the backing database view (i.e. where activity_date >= sysdate - 90, etc.), but I'd rather educate/train the user base if possible.
This probably goes without saying, but if possible, point to a separate reporting database or a logical standby database. You don't want the company pounding on your primaries and take down your order system.
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.
Spotfire is appropriate for every organization of any size because it can be a recipient of data for better decision-making. Being a robust development platform for creating reports and dashboards, creating a new Spotfire dashboard is relatively simple. Developers can create highly customized dashboards using the tools it provides. I will recommend this software to others
In an enterprise architecture, if Spotfire Advanced Data services(Composite Studio),data marts can be managed optimally and scalability in a data perspective is great. As the web player/consumer is directly proportional to RAM, if the enterprise can handle RAM requirement accomodating fail over mechanisms appropraitely, it is definitely scalable,
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.
Spotfire really helped a lot of people in terms of analysis. It eliminates data analysis in excel. Because even underlying data you can explore it in Spotfire.
Spotfire helps data analysts to investigate data and also help analysts solve inconsistency of data.
Spotfire helps data analysts in building great dashboard that provide insights to users to make decisions to drive revenue and manage the churn.