Jmp Version History — Limited Time

Data never arrives clean. It arrives in Excel spreadsheets with merged headers, missing values, and a hundred worksheets named "Final_v2." JMP 11 introduced the "JMP Data Table" and a vastly improved "Import Wizard" that could tame the wildest CSV or Excel file. It also gave us "Column Switcher"—allowing you to swap variables in a dashboard and watch all graphs update in real time. Marketing analysts wept with joy.

Enhanced Python support, direct connection to SAS Viya, and automated data cleanup alerts. JMP 17 (2022–2023)

: Brought advanced automation scripting, allowing power users to program repetitive workflows.

Introduced a 64-bit version for Mac and drag-and-drop graph building.

Added advanced data mining tools (decision trees, neural nets) and temporary Linux support. jmp version history

Built-in Text Explorer for sentiment and word analysis, interactive HTML report exporting, process screening, and formula deposition to C, Python, and JavaScript. JMP 14 & JMP Pro 14 (2018)

Interactive scatter plots, basic regression, ANOVA, and dynamically linked data tables where clicking a point highlighted it across all open charts. JMP 2 (1991)

Focused on performance and efficiency, including a 75% faster load time for certain visualizations and the new Columns Manager . It also added "Platform Presets" for saving report customizations.

Advanced DOE capabilities, time series analysis, and interactive contour plots. JMP 5 (2002) Data never arrives clean

SAS introduced JMP Pro , an advanced tier designed for predictive modeling, cross-validation, and text mining.

JMP 11 leaned heavily into the formulation industry (food, chemicals, cosmetics) and predictive analytics.

: Engineered for speed on ultra-large datasets.

This comprehensive version history traces the evolution of JMP from its Macintosh roots in 1989 to its modern, cloud-connected analytics ecosystem. The Formative Years: Macintosh Roots (1989–1993) JMP 1 (1989) Apple Macintosh exclusively. Marketing analysts wept with joy

Linux support (briefly) and deep SAS integration.

What (like DOE, Reliability, or Predictive Modeling) do you use most? Do you need to integrate your workflow with Python or R ? Share public link

Added an Excel import wizard and advanced features for Design of Experiments (DOE). JMP 10 (2012):

These versions marked a significant expansion, making JMP a true cross-platform application, fully supporting Windows alongside its traditional Macintosh user base. These versions saw improvements in data visualization techniques.