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Could someone help me automate a degradation analysis using a standalone JMP script to pull data out of an Access databasse?


Community Trekker


Nov 13, 2014

Thank you,






Jun 23, 2011

You might be able to make the script yourself with some help from JMP. Try these simple steps.

First, interactively connect to the database and use the advanced button to specify the SQL statement that will query the database for the data to be used in your analysis.

  1. Select File > Database > Table Open...
  2. Click Connect.
  3. Select Machine Data Source tab.
  4. Select the MS Access ODBC driver from the list and click OK.
  5. Navigate to the location of the database and select it, then click OK.
  6. Authenticate your access to this database if necessary.
  7. Click Advanced...
  8. Select the desired columns in the second list.
  9. Click Where...
  10. Make the Where clause here and click OK.
  11. Click Execute SQL.
  12. Click Go Back.
  13. Click Disconnect, click Yes, and then close the window..

Examine the JMP data table that results. JMP has saved the script to repeat this extraction from the database.

  1. Click on the red triangle next to the Source table script in the table panel and select Edit.
  2. Select the script and copy it (Control-C).
  3. Select File > New > Script.
  4. Paste the script (Control-V).

You are half way there.

  1. Select Analyze > Reliability and Survival > Degradation.
  2. Select the data columns and assign them to the appropriate analysis roles.
  3. Click OK.
  4. Perform any necessary actions in the platform until you are satisfied with this example as a typical analysis.
  5. Click the red triangle next to Degradation and select Script > Copy Script.
  6. Go to the script editor.
  7. Paste the script (Control-V).

You should now have a script that extracts the necessary data and performs the desired analysis without writing a single bit of code.

Best of luck!!

Learn it once, use it forever!

Community Trekker


Nov 13, 2014

Hi Mark, fantastic, I've got it! Thank you so much.  Best, R