Analytical Application Development with JMP®

Customized analytical applications and dashboards let you consolidate the most needed information of your business so you can quickly measure, analyze and act on data in the context of your organization’s processes as needed.

JMP software has always supported statistical discovery through its unique combination of interactive graphics and wealth of built-in statistics. In addition to its out-of-the-box functionality, JMP serves as an analytic hub, allowing you to quickly and easily build and share custom applications that leverage just the right JMP feature along with your other favorite analytical software.

You can call SAS, MATLAB and R to expand your data management and analytic repertoire as needed, surfacing only the required capability within JMP’s familiar point-and-click world. Once you have created your analytic application, you can take advantage of the software’s add-in architecture to package and deploy it efficiently.

Think of JMP as your personalized statistical workbench for constructing tailored applications in any problem context you choose.

Application Building and Dashboard Creation

Build and distribute analytic applications and dashboards with Application Builder and Add-In Builder in JMP. A drag-and-drop interface lets you visually design windows with buttons, lists, graphs and other objects. This saves you the step of writing scripts to create these objects. Then you write scripts to control the functionality of each object.

Application Builder also helps boost the productivity of experienced JMP Scripting Language (JSL) programmers. You can start designing a program in Application Builder and edit the automatically generated scripts. Integrate your own scripts to create even more powerful custom applications. Also create JMP add-ins, a collection of files zipped up into a single, saved file. You can access the add-in through the JMP add-ins menu. And you can share the add-in with other JMP users on the JMP File Exchange.

SAS Integration

SAS is world-renowned for its data access and data management, as well as the depth and breadth of its tried and tested analytics. JMP is a client to SAS, but designed for exploratory data visualization. JMP can work with other SAS technologies in many ways. This opportunity for integration opens up powerful SAS capabilities to new pockets of users who are already comfortable working with JMP’s intuitive dashboard. Whether you want to broaden your SAS usage to maximize your current investment – or increase the capacity of JMP’s interactive data visualization – consider building an analytical application that utilizes the extensive SAS Analytics you need in the familiar JMP environment you enjoy.

JMP and SAS Page

MATLAB Integration

Engineers who have a large investment in custom MATLAB models, programs or algorithms can interface directly to MATLAB from JMP using JSL functions in JMP. Initiate a MATLAB connection, send data to MATLAB, submit code, and bring data or output back to JMP. Or use the Application Builder in JMP to build customized GUIs, which run simulation models in MATLAB and return the results in JMP for further analysis. With JMP, you can enable others to use your MATLAB models even if they know nothing about MATLAB. To extend the functionality of JMP even further, you can use MATLAB’s external programming language interfaces to employ functionality from other languages in MATLAB, and then return the results to JMP.

Other options for JMP and MATLAB interactions include:

  • Send a JMP data table to MATLAB to use an advanced modeling technique, and then return the results to JMP for visualization and profiling.
  • Use the Custom Designer in JMP to optimize complex MATLAB models: generate experimental runs, execute a MATLAB model and return results to JMP for analysis.

R Integration

JMP integrates with the R open-source statistical programming language. This means R programmers can quickly leverage the interactive graphics in JMP to provide the much-needed multiple dynamic views that are so useful for data exploration and model interpretation. Conversely, JMP users can exploit any of the cutting-edge statistical functionality the open-source community provides – without being exposed to unnecessary and distracting complexity. You can exchange data between JMP and R, submit R code from JMP within a JMP script, and render R graphics directly in JMP. Combining these elements allows R developers who know a little JMP, or JMP developers who know a little R, to build JMP add-ins that use the advanced capabilities in R whenever they are valuable, surfacing them in a way that is appropriate for any user.

Excel Integration

With the JMP Add-In for Microsoft Excel, you can easily take your data from Excel into JMP. You can also bring the power of the JMP Profiler visualization to your Excel spreadsheets. Interactively explore what-if scenarios using the Profiler as Excel calculates the model in the background, receiving inputs from JMP and sending back outputs.


Make JMP your own…or somebody else’s. You don’t have to be a programmer to use JMP. But if you are – or if you just like to tinker – you can use the rich JMP Scripting Language (JSL) to customize, re-package, or extend JMP functionality for yourself and others. JMP allows you to automate your favorite analyses and customize reports via JSL. Its flexibility permits you to create sophisticated user interfaces, work with other analytical software, and build JMP add-ins – customized statistical discovery applications to share with other JMP users. This enables you to easily spread the use of analytics throughout your organization, wherever data is available and data-driven decisions are needed. Find an add-in or contribute one of your own in the JMP File Exchange.

Back to Top