I know what you did last summer.
If it was unintentional, then you probably don't know what I am talking about. If it was intentional, then you probably thought that I would never find out. Either way, the damage is done. The actions that you took on that warm summer evening are as clear to me now as they would have been if I had been watching over your shoulder while you did them. I know what you did last summer: You updated one of my SAS data sets.
We work on the same project and both have read, write, update, and delete rights to the project's directories. The production SAS data set that I created for the spring data delivery was inexplicably updated in the summer. And, you were the one who did it. Because we have been teammates for a while, I am giving you the benefit of the doubt. I bet that you made a copy of the production SAS program for a different use, updated it, but forgot to change the LIBREF to point to your test SAS data library. So when you ran it, you accidentally deleted 400 observations and updated 273 observations in the production data set.
Oh, you want to know how I determined it was you and how I know exactly what changed.
Well, because that production data set is very important, I used PROC DATASETS to create a SAS audit trail file for it. SAS audit trails record changes to SAS data sets. They can record the before and after image of observations that were changed, the type of change, the date/time of the change, and the userid of the person who changed the SAS data set. So, SAS audit trails can be very useful in a shared directory environment where many staff members have access to important SAS data sets.
Here is the code I used to create the audit trail for the production SAS data set:
proc datasets library=prodlib nolist; audit SpringDeliveryData; initiate; log admin_image=yes before_image=yes data_image=no error_image=yes; run; quit; |
When I executed that DATASETS procedure code, SAS created a file named SpringDeliveryData.sas7baud in the same directory as the SAS data set. When an observation is updated, added, or deleted from SpringDeliveryData, SAS writes an observation to the audit trail data set containing the variables in the original SAS data set and six specific audit trail variables. Of note are _ATDATETIME_ which specifies the date/time of the change; _ATOPCODE_ which specifies the type of change that took place--e.g. add, delete, modify; and _ATUSERID_ which specifies the userid of the person whose SAS program made the change.
When I noticed that SpringDeliveryData had been modified, I used a PROC PRINT to dump the audit trail file. That is how I know that the data set was updated at 5:27 PM on August 5th by a program submitted under your userid.
You are interested in using SAS audit trails for your own production SAS data sets? Great! You can find a comprehensive write-up in the documentation on support.sas.com at this link.
Don't fret about the updates to the SpringDeliveryData SAS data set. I am going to request that our systems administrator restore the data set to the day before the summer update. That way, we will have the original data set available in case our client has questions about it.
Good to know that I was right that you accidentally updated the production data set last summer. Oh, don't go. Unfortunately we have one more thing to talk about:
I know what you did last fall...
Best of luck in all your SAS endeavors!
1 Comment
Great post. I learned something new and it made me laugh. ;-)