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.)

The SAS data step is the most important step of a SAS program and corresponds to the step where the data are created. This tips and tricks guides you on the major statements of this step allowing you to create data in the best way.

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.

XML files are not simple line of records, they have a hierarchy and they are not easy to create programmatically. Sometimes software cannot create complex XML files and it becomes mandatory to pass through this step. In this tips and tricks, we will see how we can create XML in Data Step.

Creating or reading flat files from SAS can be done in several ways in SAS: proc import, proc export are common examples. When flat files are not simple line of records, it becomes impossible to use default technics and Data Step programming becomes required.

The SAS hash object is meant to enable you to quickly and efficiently store, search, and retrieve data based on lookup keys , Conceptually, the hash object provides programmers the means to easily define and utilize a hash table within the Data Step.

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.