SAS Viya is the latest enhancement of the SAS Platform. When you are SAS9 programmer you can continue using your SAS9 syntax in SAS Viya. However, if you want to take advantage of capabilities such as parallel processing or in memory processing offered by SAS Viya, you need to know a little bit more than SAS9 syntax.
This tips and tricks is designed for people who already know SAS9 and want to learn the basics of SAS programming in SAS Viya.

SAS Viya is the latest enhancement of the SAS Platform. When you are SAS9 programmer you can continue using your SAS9 syntax in SAS Viya. However, if you want to take advantage of capabilities such as parallel processing or in memory processing offered by SAS Viya, you need to know a little bit more than SAS9 syntax.
This tips and tricks is designed for people who already know Data Step programming in SAS9 and want to learn what you can and cannot do in SAS Data Step programming executed by the CAS server .

SAS Viya is the latest enhancement of the SAS Platform. When you are SAS9 programmer you can continue using your SAS9 syntax in SAS Viya. However, if you want to take advantage of capabilities such as parallel processing or in memory processing offered by SAS Viya, you need to know a little bit more than SAS9 syntax.
PROC FEDSQL can be executed in CAS and the syntax looks like the PROC SQL syntax. However, it is totally incorrect to say that you could copy paste Proc SQL statements/clauses into Proc FEDSQL. This tips and tricks is designed for people who already know PROC SQL and think that PROC FEDSQL is the replacement of PROC SQL.

SAS Viya is the latest enhancement of the SAS Platform. Since this release you can, as a Python programmer, access data and procedures available on the SAS Viya platform.
This can be done by inserting Python Nodes in your data flows but this can also be done thanks to the SWAT python package (SAS Scripting Wrapper for Analytics Transfer).
What does that mean? You can do with Python everything you can do in SAS: load/unload data in memory, doing parallel processing, accessing databases data via SAS libraries, working in a secured environment, use remote server. etc.
This tips and tricks is designed for people who know already Python, SQL, Pandas and who would like to access SAS Viya from Python.

Reading flat files in SAS Data Step gives you a lot of flexibility in terms of data quality and data manipulation. However, problem may arise when files are huge with poor data quality. In this tips and tricks we will have a look to the 'heart' of the Data Step manipulation and learn to do as much as we can do in this important step: applying data quality rules, creating error datasets, selecting good variables and records (etc.)

In this tips and tricks we will have a look to the merge statement of the SAS DataStep in order to combine datasets.

SAS has more than 190 of 'built-in' functions allowing you to perform a variety of programming tasks. It would be a burden to explain them all in an half day, that's the reason why we selected the most useful one in this tips and tricks.

SAS formats are instruction that SAS uses to write data values. You use formats to control the written appearance of data values, or, in some cases, to group data values together for analysis. You can create format manually with hardcoded values or from datasets, you can store them in permanent library, share them and also use build-in format (etc.) every thing you want to know about SAS format should be present in this tips and tricks.

Macro variables are tools that enable you to dynamically modify the text in a SAS program through symbolic substitution. You can assign large or small amounts of text to macro variables, when you reference the variable afterward the text that it contains will substitute the variable name.

Macro programs or Macros are compiled line of codes referred by a name that you can call anywhere in a SAS program using that name. This allows you to create SAS toolbox of code which can be used in different codes, using different parameters, using Conditional processing....

At the era of the big data, it's very common to have lot of variables to manipulate in blocks of variables. Arrays, Do loops and variable lists are powerful data manipulation tools that help make code more efficient for repetitive operation.