What You Should Know Now — and What's Next

What You Should Know Now

• How SAS programs are built from DATA steps and PROC steps, and how the DATA step loops once per row through the program data vector
• Libraries, data sets, variables, missing values, formats, and informats
• Reading data from datalines, text files, CSV, and Excel
• Conditional logic, loops, arrays, and SAS functions for text, numbers, and dates
• Combining data with SET and MERGE, and BY-group processing with FIRST. and LAST.
• Summarizing and reporting with PROC MEANS, FREQ, SQL, FORMAT, and REPORT
• Macro variables and macro programs for reusable code
• ODS output to PDF, RTF, Excel, and data sets, and graphs with PROC SGPLOT
• Linear regression, ANOVA, and logistic regression — and how to read their output
• Where SAS Viya and CAS fit, and habits that keep production SAS code reliable

What Should You Learn Next?

• Certification — the SAS Certified Specialist: Base Programming exam covers much of Levels 1 and 2 and is widely recognized by employers.
• SQL — SQL is everywhere SAS data lives; knowing it well makes PROC SQL and database work much easier.
• R — R covers the same statistical ground with free, open-source tools and a huge package ecosystem.
• Python — Python with pandas and statsmodels is the most common companion to SAS today, and SAS Viya can call it directly.

Build Something

Find a public data set you care about — sports results, weather, public health, or your own spending — and turn it into a complete SAS analysis: import, clean, summarize, model, and a report someone else could read. Put the program and the PDF on GitHub.