While the SAS DATA Step is incredibly powerful for sequential row processing, PROC SQL gives you expressive relational power, compact aggregation, and seamless macro variable integration.

1. Creating Macro Variables with INTO: Separated By

Instead of hardcoding values or writing DO-loops, you can populate a comma-delimited macro variable in a single query:

proc sql noprint;
  select quote(strip(name))
  into :subject_list separated by ', '
  from sashelp.class
  where age >= 14;
quit;

%put Selected Students: &subject_list;

2. Calculating Summaries and Re-joining Automatically

In standard SQL, calculating group percentages requires a subquery or window function. SAS PROC SQL detects aggregate functions combined with non-grouped variables and automatically re-merges the summary data back onto each row!

3. The Coalesce Function for Merges

When performing FULL JOIN operations where keys exist in both tables, coalesce() ensures you never drop subject IDs:

proc sql;
  create table merged_data as
  select coalesce(a.id, b.id) as ID,
         a.var1,
         b.var2
  from dataset_a as a
  full join dataset_b as b
    on a.id = b.id;
quit;