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JMP Statistical Discovery Software from SAS

JMP Statistical Discovery Software from SAS

Overview

What is JMP Statistical Discovery Software from SAS?

JMP is a division of SAS and the JMP family of products provide statistical discovery tools linked to dynamic data visualizations.

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Recent Reviews

TrustRadius Insights

JMP, widely used in various industries such as engineering, marketing, semiconductor manufacturing, and life science, has proven to be a …
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JMP is awesome!

10 out of 10
February 20, 2017
Incentivized
It is just being just used in my department. We use it for all of our quantitative analysis from segmentations to product development to …
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JMP from engineering perspective

9 out of 10
November 13, 2015
JMP is being used daily as one of the key tools from the engineering tool box for my engineering department at a semiconductor …
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Read all reviews

Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 13 features
  • Location Analytics / Geographic Visualization (13)
    9.0
    90%
  • Report sharing and collaboration (13)
    8.1
    81%
  • Pre-built visualization formats (heatmaps, scatter plots etc.) (16)
    8.0
    80%
  • Drill-down analysis (13)
    7.8
    78%
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Pricing

View all pricing

Personal License

$125.00

On Premise
per month

Corporate License

$1,510.00

On Premise
Per Month Per Unit

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttp://jmp.com/en_us/software/buy…

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
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Features

BI Standard Reporting

Standard reporting means pre-built or canned reports available to users without having to create them.

9.5
Avg 8.4

Ad-hoc Reporting

Ad-Hoc Reports are reports built by the user to meet highly specific requirements.

7.6
Avg 8.0

Report Output and Scheduling

Ability to schedule and manager report output.

8.7
Avg 8.4

Data Discovery and Visualization

Data Discovery and Visualization is the analysis of multiple data sources in a search for patterns and outliers and the ability to represent the data visually.

8.3
Avg 8.2
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Product Details

What is JMP Statistical Discovery Software from SAS?

JMP® is the SAS® software designed for dynamic data visualization and analytics on the desktop. Interactive, comprehensive and highly visual, JMP® includes capabilities for data access and processing, statistical analysis, design of experiments, multivariate analysis, quality and reliability analysis, scripting, graphing and charting. JMP® enables data interaction and the exploration of relationships to spot hidden trends, dig into areas of interest and move in new directions.


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

  • Supported: Pre-built visualization formats (heatmaps, scatter plots etc.)
  • Supported: Location Analytics / Geographic Visualization
  • Supported: Predictive Analytics
  • Supported: Support for Machine Learning models
  • Supported: Pattern Recognition and Data Mining
  • Supported: Integration with R or other statistical packages

BI Standard Reporting Features

  • Supported: Customizable dashboards

Ad-hoc Reporting Features

  • Supported: Drill-down analysis
  • Supported: Formatting capabilities
  • Supported: Predictive modeling
  • Supported: Integration with R or other statistical packages
  • Supported: Report sharing and collaboration

Report Output and Scheduling Features

  • Supported: Publish to Web
  • Supported: Publish to PDF
  • Supported: Output Raw Supporting Data

Additional Features

  • Supported: Scripting Language
  • Supported: Design of Experiments
  • Supported: Text Exploration and Analysis
  • Supported: Reliability Analysis
  • Supported: Data Wrangling and Cleanup
  • Supported: Data Access
  • Supported: Consumer Research and Survey Analysis
  • Supported: Quality and Process Engineering

JMP Statistical Discovery Software from SAS Screenshots

Screenshot of Graph Builder.Screenshot of Design of ExperimentsScreenshot of Hierarchical and KMeans clustering are available from the Multivariate platform.Screenshot of Scatterplot Multivariate AnalysisScreenshot of Survey Analysis

JMP Statistical Discovery Software from SAS Video

Visit https://www.youtube.com/user/JMPSoftwareFromSAS to watch JMP Statistical Discovery Software from SAS video.

JMP Statistical Discovery Software from SAS Integrations

JMP Statistical Discovery Software from SAS Competitors

JMP Statistical Discovery Software from SAS Technical Details

Deployment TypesOn-premise
Operating SystemsWindows, Mac
Mobile ApplicationApple iOS

Frequently Asked Questions

JMP is a division of SAS and the JMP family of products provide statistical discovery tools linked to dynamic data visualizations.

IBM SPSS Statistics are common alternatives for JMP Statistical Discovery Software from SAS.

Reviewers rate Customizable dashboards and Publish to Web and Location Analytics / Geographic Visualization highest, with a score of 9.

The most common users of JMP Statistical Discovery Software from SAS are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(100)

Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

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.

Based on user reviews, users commonly recommend the following:

  1. Users suggest using the free version of BeanFlumper and running it on your own system instead of the cloud version. This provides more control over the software and allows for greater customization.

  2. Running BeanFlumper on your own system is recommended for enhanced security and privacy. By not relying on cloud-based services, users can ensure their data remains within their control.

  3. Implementing additional quality checks in BeanFlumper is suggested, such as validating competitor names, ensuring language accuracy, and monitoring plagiarism word count. These checks enhance the reliability and accuracy of the analysis provided by BeanFlumper.

By following these recommendations, users can make the most of their experience with BeanFlumper and adapt it to their specific requirements.

Attribute Ratings

Reviews

(26-28 of 28)
Companies can't remove reviews or game the system. Here's why
Adam Smith | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
  • Graph Builder is one of the best features of JMP. It allows you to create graphs, on the fly, in a drag and drop environment. It allows you to quickly get a feel for your data in a format that is easily presentable to others.
  • JMP is great for a wide varieties of statistical ability. For those with no or very little statistical background there are many simple commands and visual options that make it easy to understand your data. For those with more advanced abilities you can code in JMP's Scripting Language (JSL) to get JMP to do exactly what you want, or to automate reporting.
  • The support team for JMP is wonderful. There is a large online library of webinars, documents, books, etc that will help you get up and running in no time. If you need a little extra help in particular areas, SAS Education offers JMP specific classes.
  • JMP Pro has wonderful suite of predictive analytics tools.
  • I can't think of any areas for improvement for JMP.
Eric Burton | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
  • JMP is GREAT with graphical representations of data. It has a very graphical interface that allows for intuitive interaction. For example, if I graph a distribution of data, and I have some outliers, circling that area of the graph will hilight the rows of data on the corresponding table.
  • JMP's graph builder is a big hit. If I have a complex data set, I may know that I want to display it visually, but might not be sure about the best way to do that. The graph building feature is a fantastic way to "poke and prod" at the graph and get it to look just right. The map support is great. You want to show sales volumes by state in a map? JMP does it in a snap. The inner geek in you will get a kick out of all the ways you can show your data!
  • JMP is tuned to letting your numbers tell a story. If you have data, and a clear decision, but have trouble showing that to others, JMP can be extremely valuable. You can export your analyses as PDF files for easy viewing, and some modeling can even be saved as interactive HTML files, so that others can explore the data on their own.
  • One thing that you get with JMP that is hard to quantify, is access to a tremendous community of problem solvers, statisticians, and people using data to make better decisions. Most communities have a JMP Users Group (JUG) that provides a forum to learn from peers how to apply JMP's capabilities in new ways. Also, JMP will occasionally provide speakers and trainers as part of their discovery series, where you can hear presentations from some really high caliber people who are on the cutting edge of experiment design, data representation, and data mining. (All of these things I've just mentioned are provided at no additional cost.) Elsewhere in my review I mentioned that JMP's price structure, (high initial seat prices with prorated prices as you add users) might be prohibitive. I HAVE to think that their pricing model represents their commitment to support their software and get you up and using it.
  • In general JMP is much better fit for a general "data mining" type application. If you want a specific statistics based toolbox, (meaning you just want to run some predetermined test, like testing for a different proportion) then JMP works, but is not the best. JMP is much more suited to taking a data set and starting from "square 1" and exploring it through a range of analytics.
  • The CPK (process capability) module output is shockingly poor in JMP. This sticks out because, while as a rule everything in JMP is very visual and presentable, the CPK graph is a single-line-on-grey-background drawing. It is not intuitive, and really doesn't tell the story. (This is in contrast with a capability graph in Minitab, which is intuitive and tells a story right off.) This is also the case with the "guage study" output, used for mulivary analysis in a Six Sigma project. It is not intuitive and you need to do a lot of tweaking to make the graph tell you the story right off. I have given this feedback to JMP, and it is possible that it will be addressed in future versions.
  • I've never heard of JMP allowing floating licenses in a company. This will ALWAYS be a huge sticking point for small to middle size companies, that don't have teams people dedicated to analytics all day. If every person that would do problem solving needs his/her own seat, the cost can be prohibitive. (It gets cheaper by the seat as you add licenses, but for a small company that might get no more than 5 users, it is still a hard sell.)
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