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JMP Reviews and Ratings

Rating: 9.3 out of 10
Score
9.3 out of 10

Community insights

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.

Reviews

30 Reviews

JMP Statistical Analysis Software

Rating: 10 out of 10
Incentivized

Use Cases and Deployment Scope

My organization uses JMP daily for process development, DOE, yield analysis, and SPC. It is a powerful tool and the customer support is excellent. We use JSL for automating recurring analyses.

Pros

  • DOE creation: quickly identifying variables and trials
  • DOE analysis: JMP provides clear analysis of responses
  • Yield analysis and SPC: JMP provides insights on trends and drift before parts fail.

Cons

  • There is a steep learning curve for getting started, but JMP provides great customer service to get started.
  • JSL (Jump Scripting Language) is confusing at first, but again there are some great resources and personalized help available.

Likelihood to Recommend

The price is similar to other tools but the customer support and resources available put JMP well ahead of its competition.

My review on JMP - take the time to learn and you will see the difference.

Rating: 9 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Vetted Review
JMP
10 years of experience

A statistical tool for everybody

Rating: 8 out of 10
Incentivized

Use Cases and Deployment Scope

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!

Vetted Review
JMP
1 year of experience

JMP is a great tool for beginners

Rating: 7 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Easy to use GUI, but learning JSL scripting is a steep learning curve

Rating: 7 out of 10
Incentivized

Use Cases and Deployment Scope

I use JMP Statistical Discovery Software to create statistics and data plots from large volumes of manufacturing data. The software helps to reveal manufacturing problems and anomalies, leading to cost reduction for our manufacturing.

Pros

  • Create data plots easily ( histograms, box plots, etc).
  • Generate statistics for large volumes of data.
  • Import of data into the JMP tool.

Cons

  • Better tutorials on how to write JSL scripts.
  • Need an easy way to generate a large number of statistics and plots from different variables.
  • Need more detailed documentation on how specific measurement systems analysis is calculated.

Likelihood to Recommend

JMP Statistical Discovery Software has an easy-to-use GUI to create data plots and statistics. Generating measurement system analysis (e.g. Gauge R&R) is also pretty straightforward. Learning the JSL scripting is a steep learning curve and can be difficult for some users to learn.

Vetted Review
JMP
7 years of experience

Most User Friendly Statistical Analysis Software I've Used

Rating: 10 out of 10
Incentivized

Use Cases and Deployment Scope

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.

We saved millions using JMP 4.0, what can you do with JMP 15+?

Rating: 10 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Vetted Review
JMP
20 years of experience

JMP Statistical Software - Great for quick data visualization as well as detailed analysis

Rating: 10 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Vetted Review
JMP
15 years of experience

For performing comparison analysis the best tool available in the market is JMP

Rating: 8 out of 10
Incentivized

Use Cases and Deployment Scope

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.

JMP - A user friendly statistical analysis program

Rating: 7 out of 10
Incentivized

Use Cases and Deployment Scope

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.