• Proc SQL requires few lines of SAS code compared with datastep and or Proc steps
• Frequency counting can be done in no time… which is very helpful during the QC or validation
• Proc SQL can merge datasets together using different variable names unlike datastep.
• Proc SQL can merge many datasets together in the same step on different variables
• Proc SQL allows you to join more than two datasets together at the same time on different levels
• The merge process Proc SQL join does not overlays the duplicate by-column, where the Merge statement of the data step does.
• Frequency counting can be done in no time… which is very helpful during the QC or validation
• Proc SQL can merge datasets together using different variable names unlike datastep.
• Proc SQL can merge many datasets together in the same step on different variables
• Proc SQL allows you to join more than two datasets together at the same time on different levels
• The merge process Proc SQL join does not overlays the duplicate by-column, where the Merge statement of the data step does.
Data step vs Proc SQL
• Data step Merge– Pre sorting of the dataset by the by-variable needed before the merging process
– Requires common variable names
– May need few more lines of code than Proc SQL
• PROC SQL Join process works different than the typical Data step Merge.....
– Duplicate matching columns won't be getting overlaid
– Can merge more than one dataset together, on different levels (don’t need to merge multiple datasets together using the same variable)
– Duplicate matching columns won't be getting overlaid
– Can merge more than one dataset together, on different levels (don’t need to merge multiple datasets together using the same variable)
