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First Look: SAS JMP 13 and JMP Pro 13


JMP 13 and JMP Pro 13 launched in September 2016. JMP is a business unit of SAS with more than $60M in revenue with growth and a focus in manufacturing and life sciences. Lots of engineers, analysts, researchers and scientists as users. JMP has specialty products in Genomics and Life Sciences but this release is about the core products. The tool remains focused on design of experiments, predictive modeling, quality and reliability, and consumer research though dashboards and data wrangling are being added too.

JMP 13 remains a fat client tool and with this release there are a couple of key themes:

  • Increased ease and efficiency of preparing data
  • Enriching the kinds of data and this release is adding free text
  • Handling very wide data is another area, especially as more memory is added to the desktop
  • Finally reporting, dashboards and their priority focus areas remain important

New capabilities include:

  • Lots of focus on reducing the number of clicks for actions – so for instance creating a script to recreate an analysis on new or refreshing data is now 1 click not 2.
  • JMP tables created as the software is used can now be joined using standard query builder capabilities. This essentially creates a new JMP table that can then be analyzed. This includes filters and where clauses for instance. Building the new table also prototypes the SQL that would be required on the production systems.
  • A virtual join has been added also to support situations where very tall datasets are involved. For instance, sensor data might have thousands of entries per sensor. Joining this to a table about the locations of sensors, say, might blow memory limits. The virtual join allows a join to be defined and used without ever filling the memory with joined data.
  • New dashboard building tools are included to make it easier to arrange several graphs onto a dashboard without having to go through the full application development tools. Multiple templates are provided for a simple drag and drop construction. Full interactive views (with all the support for JMP changes at runtime) or summary views are available for dashboards. Lists can be added as filters and one graph can be used to filter another – so as a user clicks on one graph, the data in the other is filtered to only those data selected in the first one.
  • Sharing reports and dashboards has been an increasing focus in recent versions. Stand-alone interactive HTML reports and dashboards have been improved. For instance, graph builder capabilities, making HTML graphs more interactive. Data for these files are embedded in the files – the data is a snapshot not live – but only the data that is needed. Multiple reports can be packaged up and an index page is generated to front end a set of independent reports.
  • JMP Pro has improved the ability to quickly organize and compare multiple models. Scripts can be published to a Formula Depot for multiple models and then used in a comparison without adding the corresponding columns to the data set. From here code can be generated for the models too – adding C, Python and Javascript to SAS and SQL.
  • Text handling has been added too. JMP allows more analysis of text using the Text Explorer which handles various languages and identifies top phrases, word clouds etc. As usual in JMP, these are interactive and can be cross-tabbed and integrated with graphs and other presentations. JMP Pro allows this to be integrated with structured data to build a model.

For more information on JMP 13 click here.


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