There is a far difference between these two. Data analysts are supposed to perform analysis or generating insights from data. Analysis can be descriptive or predictive. SAS/Excel/SQL/R are most widely used softwares in analytics industry.

SAS Programmer – More focus is there on programming in SAS (very clear from the title). Generally happens when the statistical part is well defined, or needs a rework.

Data Analyst – More inclined towards generating insights from the data, querying and preparing reports, and can also involve a bit of machine learning. This also requires programming in R/Python/SAS , however its not just programming.

This example may clarify  you:  For example, Suppose you are a bank officer. You are asked to work on a customer attrition problem. By ‘customer attrition’, i mean customers leaving the bank. You have three years historical data for customer attrition.  SAS Programmer would write a SAS program to compute average customer attrition for different bank products and present it to the higher management. He would automate the process so that the same task would be performed very quickly in future.

Whereas data analyst would write a SAS program to calculate the attrition for different products and would also see whether there is any trend in the attrition numbers.

As as an example, whether or not the attrition variety increased or decreased. that square measure the merchandise whereby attrition variety increased? And that square measure the merchandise the quantity declined. He would even be interested to visualize the profile of attritors (who left the bank). whether or not the attritors square measure high worth customers or middle /low worth customers. good analyst would take it to consecutive level and would develop a prophetical model for client attrition. He would establish the patterns of client attrition and would develop a system to cut back client attrition. however regarding automation? good analysts additionally write macros to change the repetitive task.
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