TrustRadius Insights for JMP are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Business Problems Solved
JMP, widely used in various industries such as engineering, marketing, semiconductor manufacturing, and life science, has proven to be a valuable tool for data analysis. Users have praised JMP for its user-friendly interface and ease of use in performing statistical analysis and manipulating data. This software is extensively employed for efficient design of experiments, experimental data analysis, visualization, and statistical analysis.
One of the standout features of JMP is its ability to create large amounts of graphs, including complex 3D graphs. These visualizations are highly appreciated by users who need to analyze and present data in a clear and interactive manner. Additionally, JMP finds applications in analyzing human resources data like turnover and salary reviews. It is also utilized by biotech companies to track real-time production data, quantify failures, and track efficiencies.
Furthermore, JMP is widely used in universities for meaningful statistical analyses and powerful visualization capabilities. It plays a significant role in Six Sigma and Lean programs for process optimization and formulation. In addition to that, JMP has been found useful for product evaluation, discovery, and analyzing large volumes of manufacturing data.
Users also appreciate the automation capabilities of JMP. They can use DDE in SAS or VBA in Excel to automate graph creation tasks within the software. This feature has proven to be a time-saving option when dealing with repetitive graph generation processes.
Overall, JMP serves as an indispensable tool for professionals across different industries who require robust data analysis capabilities coupled with user-friendly interfaces and flexible visualization options.
I use JMP Statistical Discovery Software from SAS to analyze and trend production data, looking for process deviations. I also use JMP Statistical Discovery Software from SAS to tabulate large datasets to understand how to pareto issues and address problems. I have used the Design of Experiments function to determine primary factors in an experiment. Finally, I used JSL to automate some tasks with large tables that needed to be merged and reorganized (split, perform a function, stack based on new column), etc.
Pros
Handles large data sets
Creates the script for a graph or table, allowing you to replicate the analysis when new data is added
Provides great flexibility using the graph builder tool
Cons
Errors in formulas are rarely diagnosed with much detail
Some preferences are hard to find (are they in the platform settings or in the drop down red arrow context menus)
Likelihood to Recommend
JMP Statistical Discovery Software from SAS deals with data much better than Excel (which is the default). Recoding data is better, merging data is easier, importing multiple files into one merged file is great, and the tabulate function is one of my favorites (much more robust than a pivot table with a cleaner output). I think Excel is a little easier to learn and better for quick analysis of a small data set where you kind of already know the answer and only need the result.
VU
Verified User
Professional in Research & Development (5001-10,000 employees)
JMP has been a commendable companion for statistical problems whether in class or with research problems for our clients who use it to extract reports.
Pros
Easy to Learn
Comprehensive statistical software
Industrial applications
Cons
Loading a large amount of data is very tedious as it takes a lot of time and it crashes very frequently.
I dislike the limited options they have in terms of statistical models or analysis tools.
Variable value designation is a big problem in JMP, the software fails to recognize the type of data when it comes to the numeric value.
Likelihood to Recommend
Overall JMP is a very good statistical tool in its features and functionalities. Initially, it does take some to learn the stuff with JMP but later that it is worth it!
VU
Verified User
Consultant in Information Technology (11-50 employees)
It is a really good product for machine learning beginners. It has a really strong point/shoot capability that makes it ideal for those who are learning how to use statistical algorithms but don't know enough to choose the right package in another system. I also like that JMP has a lot of other features that can help beginning data scientists get more familiar with and explore their data.
Pros
Machine Learning.
Data Cleaning.
Reproducible code.
Cons
I like it when I can type in the code myself and although there was a print and save code option from the menus, I could not have produced the code myself in an easy-to-use console.
Likelihood to Recommend
I think JMP works best for beginners. It helps students get a really firm grasp on the algorithms and choose how to evaluate them. That being said, I think that any data scientist should move to R or Python as quickly as possible so they can take advantage of a wider range of options and flexibility.
JMP is incredibly user friendly. It is such a fast, easy and integral tool in data management and quickly analyzing and presenting results in a user-friendly fashion. It helps us track changes in population, census data, and identifying areas of need in across numerous socioeconomic factors in the populations we serve.
Pros
Finding population averages
Tracking changes instituted with project funding
Cons
Downloading results and integrating them into other software is difficult with certain CRMS
Likelihood to Recommend
Query Builder saves time in configuring multiple tables and JMP is particularly adept at seamlessly importing data across many formats. I find it much more preferable than SAS, is very user friendly, and doesn't require writing code. I really can't think of a scenario in which I use another format to store and analyze population data for my work.
JMP is in use for our Six Sigma and Lean programs at the organizational level. The software has a yearly corporate license program due to its widespread use.
Pros
Data exploration.
Visual statistical analyses.
Rapid acceptance by novice users.
Excellent public forums for assistance with uncommon challenges.
Outstanding technical support.
Great people creating a great product.
Cons
Interactive platforms could be better, especially when trying to use exported interactive graphics.
Improved 'bailout' when the user needs to stop the 'spinning ball' associated with prolonged calculations.
Expanded descriptions as to strategies using neural and other higher end ML programming. Hard to know the approach for choosing the number of nodes, trials, etc. The webinars are helpful but a bit more clarity would be helpful.
Dependent calculations made with custom formatting (e.g., use of currency) for subsequent derivative calculations should also show in the same (currency) format.
Likelihood to Recommend
I have found it particularly well suited in exploring small to large datasets (10-10M rows) as long as you have a reasonably fast computer equipped with sufficient RAM (32 Gb+). The graphics packages are very helpful in exploring expected as well as new potential relationships between data factors. The analytic packages have been used with excellent effect and have directly resulted in identifying system-level errors or opportunities which in turn have resulted in millions of dollars in recovered revenue as well as cost savings.
Like all effective power tools, JMP has to be used with care. At a push of a button, it will give you a result, even very significant results, but it still takes an experienced user to determine the useful significance of a 'statistically significant result' based on thousands of observations.
VU
Verified User
Professional in Research & Development (10,001+ employees)
JMP Statistical Software is used at our company by specific individuals when called upon by various departments. The software has been used for product evaluation and discovery including Design of Experiments as well as for human resources data such as turnover and salary reviews. By using JMP Software we can quickly see what the data is telling us about a given situation.
Pros
JMP Software allows for quick data visualization
JMP Software is easy to use and can be learned very quickly
JMP Software can be used for detailed statistical analysis using multiple formats and calculations.
Cons
JMP Software is continuously adding new features.
I do not have any current recommendations for changes to the software.
Likelihood to Recommend
JMP Software is well-suited for data analysis in all forms. It can be used for quickly viewing data using the chart builder or for more in-depth analysis using statistical evaluations. The only time I do not transfer my data to a JMP data table is when I have just a few data points and I can make a chart in excel just as quickly.
VU
Verified User
Professional in Human Resources (501-1000 employees)
This is used account-wise to compare the statistical inferences of the data through graphs. I used this tool to understand the customer churning ratio. The results were more detailed oriented and pretty much easy to understand. We also used this tool in understanding the pattern of primary research data on the comparison of the opinions of the users of medical services.
Pros
Graphs are more detail-oriented and contain statistical inferences.
Everything is drag and drop. Pretty much easy to use and handle and also to learn.
Importing and exporting the results are easy and they can be attached with any other tool for processing.
Cons
Basic cleaning of the data is not that easy and few options are available.
Very limited JMP communities are available on internet.
While loading big data, it crashes many times.
Likelihood to Recommend
Understanding data is best for doing comparisons. To understanding our customer churning ratio we compared multiple factors and this tool was pretty handy. We checked the customer data of similar-profile companies in different locations and results were the very best.
While doing analysis on the data where the data contained more than 75 lac rows, this tool was very disappointing and we were unable to clean the data in it.
We started out with only a small group using JMP, but due to its ease of use, we have now expanded it so that almost everyone doing any kind of statistical analysis is using JMP. It is our go-to choice for fast and easy statistical analysis products and is the favorite for new workers.
Pros
No coding required!
Fast, easy, and simple.
Microsoft Excel compatible.
Cons
Not many in-depth tools compared to other programs.
Non-open source for quick and easy fixes to bugs.
Expensive compared to other programs.
Likelihood to Recommend
JMP is a really excellent program for providing quick and easy statistical analysis of large and complex data sets. It is extremely user-friendly since it does not require coding, and this makes it a very versatile program for a whole organization. The main area where it is not quite as useful is in performing very specific or complex processes - it lacks many of those powerful tools found in other programs.
I use SAS JMP for all kinds of statistical analysis; from data analysis and visualisation to modeling. Another huge part of the work allowed by JMP is the design of experiment. It allows for the recording, analysis and visualisation of vast quantities of data while remaining user-friendly.
Pros
Design of experiment: it is a very powerful feature of this software. Unlike other software I tried out, JMP remains user-friendly while providing complete and sophisticated analysis parameters.
Data visualisation: JMP provides various data visualisation options that can treat easily vast quantities of data in an intuitive way.
Data recording: JMP allows for easy manipulation of vast quantities of data. It is extremely easy to reformat, amend, pivot and export data to new tables. Never before working with data had been made so simple.
Cons
JMP assumes a lot of statistical knowledge from the user. On the more esoteric analysis, I would like some explanation on why I use such or such method.
Likelihood to Recommend
JMP is perfect in my environment, research and development, where I must design experiments efficiently to test many parameters, generate large amounts of data that I need to analyse to discover effects or trends. As well as to test process robustness.
I worked in student-led marketing consulting firm and I led the Analytics and Insights team, and we used JMP for data analysis. There were around 50 people in the organization, but only the ones in the Analytics and Insights department used JMP. We received requests from the account managers and we then ran some analysis for them depending on the project need.
Pros
1 - Coding is not required: I've used other tools (Python, Mathlab, and R) and coding is required for all of them. With JMP, you just load the data, see it in a table and start working right away. I see it as a statistical version of MS Excel.
2 - Powerful and easy regression: I love how easy, intuitive and powerful JMP is for running regression models. It was great for trying to fit the best regression models.
3 - Smooth OS integration: I use in both macOS and Windows and both run just fine!
Cons
1 - Not the most user friendly: In comparison to other tools (Azure ML, for example), JMP is not the most user friendly.
2 - Features are not super comprehensive: Don't get me wrong, JMP has a lot of features! But when you compare against R, which is open source - so there are a lot of people adding new libraries frequently, JMP might lack some things you might want (especially the most recent ones).
3 - Cost: In comparison to others (Azure ML is super cheap, R and Python are free), JMP can seem expensive.
Likelihood to Recommend
Well suited: - If you are using a lot of data tables, and would like the best tool to run regression;
Less appropriate: - If you want to run some of the newest machine learning models; - If you are on a budget and still want to get the best of your datasets.