JMP Statistical Discovery Software from SAS Reviews

65 Ratings
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Score 8.5 out of 101

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Akshaya Bhardwaj profile photo
Score 8 out of 10
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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.
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Shelby Bowden profile photo
Score 7 out of 10
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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.
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Score 10 out of 10
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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.
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Score 8 out of 10
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This has worked well when pulling data from similar sources like servers, etc. It has not worked well when you are trying to pull data from multiple different kinds of sources. The errors at that time are difficult to troubleshoot and you almost need to be an expert to move ahead.
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Score 10 out of 10
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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.
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Thibaut Angevin profile photo
Score 10 out of 10
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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.
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Gabriel Chiararia profile photo
Score 9 out of 10
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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.
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Score 8 out of 10
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JMP is great for crunching huge datasets, especially if you are overloading your Excel workbook. You can have JMP communicate directly with Excel or FileMaker because it has its own scripting language, so you can basically have report at the click of a button. If you are into formatting and pretty graphs, JMP does not include a ton of aesthetic functionality. The drag and drop graph building function allows you to filter out variables easily and change the look of your graph, but can be confusing at times even when you are trying to create simple graphs. Overall it is a great tool to crunch a lot of data without lag.
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Roberto Jimenez profile photo
Score 9 out of 10
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Likelihood to Recommend

Well suited for preliminary data analysis, identifying trends and distribution of the data, finding and excluding outliers as appropriate. Since JMP is well equipped for exploratory analysis, it is not the best choice when the level of interaction with the data must be limited.
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Wayne Levin profile photo
Score 10 out of 10
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Likelihood to Recommend

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.
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Ruth Wirawan profile photo
Score 10 out of 10
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Likelihood to Recommend

Reliability module: Parametric survival analysis platform is powerful, however, the translation to common physics of failure models can be unclear. Proper documentation and live pop-up explanations will be very helpful. Often times, I have to rerun the same data sets in Reliasoft ALTA Pro to confirm my interpretation of the parameters is correct.
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Michael Carcasi profile photo
Score 10 out of 10
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Likelihood to Recommend

JMP is a powerful data visualization tool. It likewise is a powerful DOE tool. For these applications, I think it is appropriate for all. As you dive deeper into JMP capabilities, I think it becomes more appropriate for user to have at least some formal training in statistics.
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Mark Davis profile photo
Score 7 out of 10
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Likelihood to Recommend

Data size and complexity is the driver for choice of an analysis application. For example, a thousand line by 150 column data set is great for excel or a spreadsheet. If the data is in the 25,000 line range and only a 100 columns then use JMP. For larger and more complex relational databases my recommendation is for SAS.
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Eric Burton profile photo
Score 8 out of 10
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Likelihood to Recommend

Are you interested in high level data mining? Does your team participate in a lot of Statistically Designed Experiments? (DOE) JMP does very well here. Are you performing response modeling and creating prediction equations? JMP does this very well. Are you focused on good looking, graphical representations of your data? JMP SHINES in the presentation arena. Do you have some "stats geeks" on staff that know the numbers, but want a fast way to share reporting with others? JMP is a good avenue for this.

However, are you looking for a "quick and dirty" stats toolbox for SPC/control charting, for CPK analyses, t-tests or proportion testing? Are you looking for a "vending machine" interaction where you know exactly what you want and you just want one output? If the above describes you more closely, I'd suggest something closer to Minitab.
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Michael Morris profile photo
Score 5 out of 10
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Likelihood to Recommend

JMP, like other point and click analysis environments, are very useful to users with little or no programming experience. A typical analyst who has experience in data analysis would much prefer to code their analysis programs than using a point and click environment. However for users without a strong analysis background who are using JMP for simple purposes, the point and click environment can be very user friendly for them. But as I mentioned, the inability to code can deter more advanced users.
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Camilo Silva profile photo
Score 9 out of 10
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Likelihood to Recommend

WELL SUITED
High throughput data analysis that need all kinds of statistics and graphs

NOT WELL SUITED
Business reporting and graph creation and customization (like Excel)
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Adam Smith profile photo
Score 10 out of 10
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Likelihood to Recommend

JMP is well-suited to a variety of applications. It is often used by engineers and analysts who may not be experts in statistics, but know enough to successfully use JMP to produce great analysis. JMP is a product created by SAS, which is a great company to work with. If you get the opportunity to attend the JMP Discovery Summit (JMP's annual conference in September) it is a great opportunity to learn more about the product both from the developers as well as from fellow users.
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February 20, 2017

JMP is awesome!

Score 10 out of 10
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Likelihood to Recommend

Better for smaller datasets that aren't querying millions of rows of data.
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Score 9 out of 10
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Likelihood to Recommend

It is perfectly suited for statistical analyses, but I would not recommend JMP for users who do not have a statistical background. As previously stated, the learning curve is exceptionally steep, and I think that it would prove to be too steep for those without statistical background/knowledge.
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Score 9 out of 10
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Likelihood to Recommend

JMP is well suited for statistical analysis. However, when underlying physics or science is needed to better understand or simulate the observation or to provide prediction by modeling, JMP seems to lack the flexibility for end-user to provide boundary conditions or pre-defined rules to rule out impossibles in the predictive modeling.
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Score 8 out of 10
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Likelihood to Recommend

Pros:
Do you need Visual Analytics?
Is your data noisy?
Are you new to statistics and analysis? Good Documentation
Do you need for DOE? Easy for simple DOE and modeling cases
Do you need to interface with other softwares? Capability to interface with other programs like R, Matlab, Excel etc...

Cons:
Do you need to automate repetitive tasks? Scripting is not friendly and needs improvement
Do you need to build an application? Application Builder is a good addition but at infancy phase
Do you need for data mining? Data Mining algorithms not yet sophisticated
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Score 6 out of 10
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Likelihood to Recommend

I think it is less appropriate for professional looking printed reports. If you are looking for a tool to give to non-programmers so they can look at relationships themselves without bothering you, or are looking to automate graphs, this would work very well for you. It would also be useful if you wanted to make 3D graphs that can be embedded, because they can be spun with the cursor. Of course, you cannot do this in a printed report.
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Feature Scorecard Summary

Pixel Perfect reports (1)
10
Customizable dashboards (9)
8.7
Drill-down analysis (11)
8.9
Formatting capabilities (11)
8.9
Integration with R or other statistical packages (8)
8.1
Report sharing and collaboration (10)
9.0
Publish to Web (7)
7.9
Publish to PDF (9)
9.5
Report Versioning (1)
7
Report Delivery Scheduling (1)
10
Pre-built visualization formats (heatmaps, scatter plots etc.) (13)
8.7
Location Analytics / Geographic Visualization (10)
9.0
Predictive Analytics (10)
8.8

About JMP Statistical Discovery Software from SAS

JMP®

JMP® is the SAS® software designed for dynamic data visualization and analytics on the desktop. Interactive, comprehensive and highly visual, JMP® includes comprehensive capabilities for data access and processing, statistical analysis, design of experiments, multivariate analysis, quality and reliability analysis, scripting, graphing and charting, and more. According to the vendor, JMP® enables data interaction and the exploration of relationships to spot hidden trends, dig into areas of interest and move in new directions that hadn’t yet been considered.

JMP® Pro

JMP® Pro is the advanced analytics version of JMP® statistical discovery software from SAS®. JMP® Pro provides superior visual data access and manipulation, interactive, comprehensive analyses and extensibility (according to the vendor, these are the hallmarks of JMP), plus a many additional techniques. With JMP® Pro, users get the power of predictive modeling with cross-validation, advanced consumer research and reliability analysis, statistical modeling and bootstrapping in desktop-based environment. JMP® Pro is designed for use cases where large data volumes are present, or data is messy, includes outliers or missing data and users want to employ data mining methods or build predictive models that generalize well.

JMP Statistical Discovery Software from SAS Features

Data Discovery and Visualization Features
Has featurePre-built visualization formats (heatmaps, scatter plots etc.)
Has featureLocation Analytics / Geographic Visualization
Has featurePredictive Analytics
Has featureSupport for Machine Learning models
Has featurePattern Recognition and Data Mining
Has featureIntegration with R or other statistical packages
BI Standard Reporting Features
Has featureCustomizable dashboards
Does not have featureReport Formatting Templates
Does not have featurePixel Perfect reports
Ad-hoc Reporting Features
Has featureDrill-down analysis
Has featureFormatting capabilities
Has featurePredictive modeling
Has featureIntegration with R or other statistical packages
Has featureReport sharing and collaboration
Report Output and Scheduling Features
Has featurePublish to Web
Has featurePublish to PDF
Has featureOutput Raw Supporting Data
Does not have featureReport Versioning
Does not have featureReport Delivery Scheduling
Does not have featureDelivery to Remote Servers
Additional Features
Has featureScripting Language
Has featureDesign of Experiments
Has featureText Exploration and Analysis
Has featureReliability Analysis
Has featureData Wrangling and Cleanup
Has featureData Access
Has featureConsumer Research and Survey Analysis
Has featureQuality and Process Engineering

JMP Statistical Discovery Software from SAS Screenshots

JMP Statistical Discovery Software from SAS Integrations

MATLAB, R, SAS

JMP Statistical Discovery Software from SAS Competitors

IBM SPSS, Reliasoft, Minitab

Pricing

Has featureFree Trial Available?Yes
Does not have featureFree or Freemium Version Available?No
Does not have featurePremium Consulting/Integration Services Available?No
Entry-level set up fee?No

JMP Statistical Discovery Software from SAS Support Options

 Free VersionPaid Version
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JMP Statistical Discovery Software from SAS Technical Details

Deployment Types:On-premise
Operating Systems: Windows, Mac
Mobile Application:Apple iOS