SAS to Databricks

Why teams move now

• Viya & license pressure. Renewals climb while cloud analytics wins budget.
• Talent cliff. Nobody under 40 knows SAS; Python/SQL is the hiring market.
• Macro libraries. %DO-generated SQL is where DIY rewrites stall.

Hardest construct — sanitized peek

Enough to judge fit. Not a rebuild-the-parser cookbook.

Before
%macro dyn(tables);
  %do i=1 %to %sysfunc(countw(&tables));
    %let t=%scan(&tables,&i);
    proc sql; create table out_&t as select * from &t; quit;
  %end;
%mend;

After (databricks)
for t in tables:
    spark.table(t).write.mode('overwrite').saveAsTable(f'out_{t}')

What good looks like

Parser-driven conversion, readable databricks output, and row-level parity before cutover. Upload a sample or run a pilot on your estate — no email gate to peek.